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You searched for subject:(Signal classification). Showing records 1 – 30 of 426 total matches.

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Virginia Tech

1. Ramkumar, Barathram. Automatic Modulation Classication and Blind Equalization for Cognitive Radios.

Degree: PhD, Electrical and Computer Engineering, 2011, Virginia Tech

 Cognitive Radio (CR) is an emerging wireless communications technology that addresses the inefficiency of current radio spectrum usage. CR also supports the evolution of existing… (more)

Subjects/Keywords: signal classification; blind equalization

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APA (6th Edition):

Ramkumar, B. (2011). Automatic Modulation Classication and Blind Equalization for Cognitive Radios. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28666

Chicago Manual of Style (16th Edition):

Ramkumar, Barathram. “Automatic Modulation Classication and Blind Equalization for Cognitive Radios.” 2011. Doctoral Dissertation, Virginia Tech. Accessed August 13, 2020. http://hdl.handle.net/10919/28666.

MLA Handbook (7th Edition):

Ramkumar, Barathram. “Automatic Modulation Classication and Blind Equalization for Cognitive Radios.” 2011. Web. 13 Aug 2020.

Vancouver:

Ramkumar B. Automatic Modulation Classication and Blind Equalization for Cognitive Radios. [Internet] [Doctoral dissertation]. Virginia Tech; 2011. [cited 2020 Aug 13]. Available from: http://hdl.handle.net/10919/28666.

Council of Science Editors:

Ramkumar B. Automatic Modulation Classication and Blind Equalization for Cognitive Radios. [Doctoral Dissertation]. Virginia Tech; 2011. Available from: http://hdl.handle.net/10919/28666


University of Cincinnati

2. ALQADAH, HATIM FAROUQ. OPTIMIZED TIME-FREQUENCY CLASSIFICATION METHODS FOR INTELLIGENT AUTOMATIC JETTISONING OF HELMET-MOUNTED DISPLAY SYSTEMS.

Degree: MS, Engineering : Electrical Engineering, 2007, University of Cincinnati

 Helmet-Mounted Display Systems (HMDS) improve the effectiveness of air force pilots in combat. The embedded display systems provide the pilot with vital aircraft information, “look… (more)

Subjects/Keywords: Time-Frequency; Signal Detection; Signal Classification; Detection Algorithm

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APA (6th Edition):

ALQADAH, H. F. (2007). OPTIMIZED TIME-FREQUENCY CLASSIFICATION METHODS FOR INTELLIGENT AUTOMATIC JETTISONING OF HELMET-MOUNTED DISPLAY SYSTEMS. (Masters Thesis). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1185838368

Chicago Manual of Style (16th Edition):

ALQADAH, HATIM FAROUQ. “OPTIMIZED TIME-FREQUENCY CLASSIFICATION METHODS FOR INTELLIGENT AUTOMATIC JETTISONING OF HELMET-MOUNTED DISPLAY SYSTEMS.” 2007. Masters Thesis, University of Cincinnati. Accessed August 13, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1185838368.

MLA Handbook (7th Edition):

ALQADAH, HATIM FAROUQ. “OPTIMIZED TIME-FREQUENCY CLASSIFICATION METHODS FOR INTELLIGENT AUTOMATIC JETTISONING OF HELMET-MOUNTED DISPLAY SYSTEMS.” 2007. Web. 13 Aug 2020.

Vancouver:

ALQADAH HF. OPTIMIZED TIME-FREQUENCY CLASSIFICATION METHODS FOR INTELLIGENT AUTOMATIC JETTISONING OF HELMET-MOUNTED DISPLAY SYSTEMS. [Internet] [Masters thesis]. University of Cincinnati; 2007. [cited 2020 Aug 13]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1185838368.

Council of Science Editors:

ALQADAH HF. OPTIMIZED TIME-FREQUENCY CLASSIFICATION METHODS FOR INTELLIGENT AUTOMATIC JETTISONING OF HELMET-MOUNTED DISPLAY SYSTEMS. [Masters Thesis]. University of Cincinnati; 2007. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1185838368


Virginia Tech

3. Chavali, Venkata Gautham. Signal Detection and Modulation Classification in Non-Gaussian Noise Environments.

Degree: PhD, Electrical and Computer Engineering, 2012, Virginia Tech

Signal detection and modulation classification are becoming increasingly important in a variety of wireless communication systems such as those involving spectrum management and electronic warfare… (more)

Subjects/Keywords: Modulation classification; Non-Gaussian noise; Signal detection

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APA (6th Edition):

Chavali, V. G. (2012). Signal Detection and Modulation Classification in Non-Gaussian Noise Environments. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/28387

Chicago Manual of Style (16th Edition):

Chavali, Venkata Gautham. “Signal Detection and Modulation Classification in Non-Gaussian Noise Environments.” 2012. Doctoral Dissertation, Virginia Tech. Accessed August 13, 2020. http://hdl.handle.net/10919/28387.

MLA Handbook (7th Edition):

Chavali, Venkata Gautham. “Signal Detection and Modulation Classification in Non-Gaussian Noise Environments.” 2012. Web. 13 Aug 2020.

Vancouver:

Chavali VG. Signal Detection and Modulation Classification in Non-Gaussian Noise Environments. [Internet] [Doctoral dissertation]. Virginia Tech; 2012. [cited 2020 Aug 13]. Available from: http://hdl.handle.net/10919/28387.

Council of Science Editors:

Chavali VG. Signal Detection and Modulation Classification in Non-Gaussian Noise Environments. [Doctoral Dissertation]. Virginia Tech; 2012. Available from: http://hdl.handle.net/10919/28387


Coventry University

4. Balasubramanian, R. K. Development of novel approaches for high resolution direction of arrival estimation techniques.

Degree: PhD, 2016, Coventry University

 This thesis presents the development of MUSIC algorithm based novel approaches for the estimation of Direction of Arrival (DOA) of electromagnetic sources. For the 2D-DOA… (more)

Subjects/Keywords: 621.382; Antenna arrays; Multiple signal classification

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APA (6th Edition):

Balasubramanian, R. K. (2016). Development of novel approaches for high resolution direction of arrival estimation techniques. (Doctoral Dissertation). Coventry University. Retrieved from http://curve.coventry.ac.uk/open/items/576a5aa1-32f8-4c01-99fa-a9023d7a1fc5/1 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.699444

Chicago Manual of Style (16th Edition):

Balasubramanian, R K. “Development of novel approaches for high resolution direction of arrival estimation techniques.” 2016. Doctoral Dissertation, Coventry University. Accessed August 13, 2020. http://curve.coventry.ac.uk/open/items/576a5aa1-32f8-4c01-99fa-a9023d7a1fc5/1 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.699444.

MLA Handbook (7th Edition):

Balasubramanian, R K. “Development of novel approaches for high resolution direction of arrival estimation techniques.” 2016. Web. 13 Aug 2020.

Vancouver:

Balasubramanian RK. Development of novel approaches for high resolution direction of arrival estimation techniques. [Internet] [Doctoral dissertation]. Coventry University; 2016. [cited 2020 Aug 13]. Available from: http://curve.coventry.ac.uk/open/items/576a5aa1-32f8-4c01-99fa-a9023d7a1fc5/1 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.699444.

Council of Science Editors:

Balasubramanian RK. Development of novel approaches for high resolution direction of arrival estimation techniques. [Doctoral Dissertation]. Coventry University; 2016. Available from: http://curve.coventry.ac.uk/open/items/576a5aa1-32f8-4c01-99fa-a9023d7a1fc5/1 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.699444


Louisiana State University

5. Edwards, Charisma Dionne. Psychological Behavior Analysis Using Advanced Signal Processing Techniques for fMRI Data.

Degree: PhD, Electrical and Computer Engineering, 2013, Louisiana State University

 Psychological analysis related to voluntary reciprocal trust games were obtained using functional magnetic resonance imaging (fMRI) hyperscanning for 44 pairs of strangers throughout 36 trust… (more)

Subjects/Keywords: leave-one-out; leave-half-out; biomedical signal processing; social signal processing; behavioral signal processing; signal processing; prediction; classification

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APA (6th Edition):

Edwards, C. D. (2013). Psychological Behavior Analysis Using Advanced Signal Processing Techniques for fMRI Data. (Doctoral Dissertation). Louisiana State University. Retrieved from etd-11182013-162101 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1954

Chicago Manual of Style (16th Edition):

Edwards, Charisma Dionne. “Psychological Behavior Analysis Using Advanced Signal Processing Techniques for fMRI Data.” 2013. Doctoral Dissertation, Louisiana State University. Accessed August 13, 2020. etd-11182013-162101 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1954.

MLA Handbook (7th Edition):

Edwards, Charisma Dionne. “Psychological Behavior Analysis Using Advanced Signal Processing Techniques for fMRI Data.” 2013. Web. 13 Aug 2020.

Vancouver:

Edwards CD. Psychological Behavior Analysis Using Advanced Signal Processing Techniques for fMRI Data. [Internet] [Doctoral dissertation]. Louisiana State University; 2013. [cited 2020 Aug 13]. Available from: etd-11182013-162101 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1954.

Council of Science Editors:

Edwards CD. Psychological Behavior Analysis Using Advanced Signal Processing Techniques for fMRI Data. [Doctoral Dissertation]. Louisiana State University; 2013. Available from: etd-11182013-162101 ; https://digitalcommons.lsu.edu/gradschool_dissertations/1954


Penn State University

6. Vu, Tiep. Signal classification under structured sparsity constraints.

Degree: 2019, Penn State University

 Object Classification is a key direction of research in signal and image processing, computer vision and artificial intelligence. The goal is to come up with… (more)

Subjects/Keywords: Signal Classification; Sparsity Coding; Dictionary Learning; Image Classification; Optimization

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APA (6th Edition):

Vu, T. (2019). Signal classification under structured sparsity constraints. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/16112thv102

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Vu, Tiep. “Signal classification under structured sparsity constraints.” 2019. Thesis, Penn State University. Accessed August 13, 2020. https://submit-etda.libraries.psu.edu/catalog/16112thv102.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Vu, Tiep. “Signal classification under structured sparsity constraints.” 2019. Web. 13 Aug 2020.

Vancouver:

Vu T. Signal classification under structured sparsity constraints. [Internet] [Thesis]. Penn State University; 2019. [cited 2020 Aug 13]. Available from: https://submit-etda.libraries.psu.edu/catalog/16112thv102.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Vu T. Signal classification under structured sparsity constraints. [Thesis]. Penn State University; 2019. Available from: https://submit-etda.libraries.psu.edu/catalog/16112thv102

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Purdue University

7. Du, Yuezhi. Signal enhancement and data mining for biological and chemical samples using mass spectrometry.

Degree: PhD, Biomedical Engineering, 2015, Purdue University

 Mass spectrometry has been actively involved in the areas of healthcare, pharmaceutics, environmental analysis, food industry and forensics due to its ability to provide molecular… (more)

Subjects/Keywords: Biomarker identification; Data mining; Mass spectrometry; Sample classification; Signal enhancement; Signal processing

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APA (6th Edition):

Du, Y. (2015). Signal enhancement and data mining for biological and chemical samples using mass spectrometry. (Doctoral Dissertation). Purdue University. Retrieved from https://docs.lib.purdue.edu/open_access_dissertations/1110

Chicago Manual of Style (16th Edition):

Du, Yuezhi. “Signal enhancement and data mining for biological and chemical samples using mass spectrometry.” 2015. Doctoral Dissertation, Purdue University. Accessed August 13, 2020. https://docs.lib.purdue.edu/open_access_dissertations/1110.

MLA Handbook (7th Edition):

Du, Yuezhi. “Signal enhancement and data mining for biological and chemical samples using mass spectrometry.” 2015. Web. 13 Aug 2020.

Vancouver:

Du Y. Signal enhancement and data mining for biological and chemical samples using mass spectrometry. [Internet] [Doctoral dissertation]. Purdue University; 2015. [cited 2020 Aug 13]. Available from: https://docs.lib.purdue.edu/open_access_dissertations/1110.

Council of Science Editors:

Du Y. Signal enhancement and data mining for biological and chemical samples using mass spectrometry. [Doctoral Dissertation]. Purdue University; 2015. Available from: https://docs.lib.purdue.edu/open_access_dissertations/1110


Brno University of Technology

8. Matuštík, Daniel. Parametrická analýza zvuků: Parametrical analysis of sound.

Degree: 2018, Brno University of Technology

 This bachelor's thesis deals with the processing of acoustic signal. The work includes theoretical models for the processing and classification and shows the spectrogram fuss… (more)

Subjects/Keywords: Analýza; parametrizace; klasifikace; zpracování signálů; akustický signál.; Analysis; parameterization; classification; signal processing; acoustic signal.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Matuštík, D. (2018). Parametrická analýza zvuků: Parametrical analysis of sound. (Thesis). Brno University of Technology. Retrieved from http://hdl.handle.net/11012/16332

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Matuštík, Daniel. “Parametrická analýza zvuků: Parametrical analysis of sound.” 2018. Thesis, Brno University of Technology. Accessed August 13, 2020. http://hdl.handle.net/11012/16332.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Matuštík, Daniel. “Parametrická analýza zvuků: Parametrical analysis of sound.” 2018. Web. 13 Aug 2020.

Vancouver:

Matuštík D. Parametrická analýza zvuků: Parametrical analysis of sound. [Internet] [Thesis]. Brno University of Technology; 2018. [cited 2020 Aug 13]. Available from: http://hdl.handle.net/11012/16332.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Matuštík D. Parametrická analýza zvuků: Parametrical analysis of sound. [Thesis]. Brno University of Technology; 2018. Available from: http://hdl.handle.net/11012/16332

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

9. Safi, Khaled. Human postural stability analysis : application to Parkinsonian subjects : Méthodes d'analyse de la stabilité posturale chez l'homme : application aux sujets Parkinsoniens.

Degree: Docteur es, Signal, Image, Automatique, 2016, Université Paris-Est

L’analyse de la stabilité posturale chez l’homme a fait l’objet, ces dernières années, d’un intérêt grandissant au sein de la communauté scientifique. Le système postural… (more)

Subjects/Keywords: Analyse posturale; Stabilométrie; Décomposition du signal; Classification; Hmm; Maladie de Parkinson; Posture; Stabilometry; Signal decomposition; Classification; Hmm; Parkinson's disease

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APA (6th Edition):

Safi, K. (2016). Human postural stability analysis : application to Parkinsonian subjects : Méthodes d'analyse de la stabilité posturale chez l'homme : application aux sujets Parkinsoniens. (Doctoral Dissertation). Université Paris-Est. Retrieved from http://www.theses.fr/2016PESC1066

Chicago Manual of Style (16th Edition):

Safi, Khaled. “Human postural stability analysis : application to Parkinsonian subjects : Méthodes d'analyse de la stabilité posturale chez l'homme : application aux sujets Parkinsoniens.” 2016. Doctoral Dissertation, Université Paris-Est. Accessed August 13, 2020. http://www.theses.fr/2016PESC1066.

MLA Handbook (7th Edition):

Safi, Khaled. “Human postural stability analysis : application to Parkinsonian subjects : Méthodes d'analyse de la stabilité posturale chez l'homme : application aux sujets Parkinsoniens.” 2016. Web. 13 Aug 2020.

Vancouver:

Safi K. Human postural stability analysis : application to Parkinsonian subjects : Méthodes d'analyse de la stabilité posturale chez l'homme : application aux sujets Parkinsoniens. [Internet] [Doctoral dissertation]. Université Paris-Est; 2016. [cited 2020 Aug 13]. Available from: http://www.theses.fr/2016PESC1066.

Council of Science Editors:

Safi K. Human postural stability analysis : application to Parkinsonian subjects : Méthodes d'analyse de la stabilité posturale chez l'homme : application aux sujets Parkinsoniens. [Doctoral Dissertation]. Université Paris-Est; 2016. Available from: http://www.theses.fr/2016PESC1066

10. Chan wai tim, Stefen. Apprentissage supervisé d’une représentation multi-couches à base de dictionnaires pour la classification d’images et de vidéos : Supervised Multi-layer Dictionary learning for image and video classification.

Degree: Docteur es, Signal image parole telecoms, 2016, Université Grenoble Alpes (ComUE)

Ces dernières années, de nombreux travaux ont été publiés sur l'encodage parcimonieux et l'apprentissage de dictionnaires. Leur utilisation s'est initialement développée dans des applications de… (more)

Subjects/Keywords: Traitement du signal; Classification; Apprentissage; Dictionnaire; Parcimonie; Signal processing; Classification; Machine learning; Dictionary; Sparse Coding; 620

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APA (6th Edition):

Chan wai tim, S. (2016). Apprentissage supervisé d’une représentation multi-couches à base de dictionnaires pour la classification d’images et de vidéos : Supervised Multi-layer Dictionary learning for image and video classification. (Doctoral Dissertation). Université Grenoble Alpes (ComUE). Retrieved from http://www.theses.fr/2016GREAT089

Chicago Manual of Style (16th Edition):

Chan wai tim, Stefen. “Apprentissage supervisé d’une représentation multi-couches à base de dictionnaires pour la classification d’images et de vidéos : Supervised Multi-layer Dictionary learning for image and video classification.” 2016. Doctoral Dissertation, Université Grenoble Alpes (ComUE). Accessed August 13, 2020. http://www.theses.fr/2016GREAT089.

MLA Handbook (7th Edition):

Chan wai tim, Stefen. “Apprentissage supervisé d’une représentation multi-couches à base de dictionnaires pour la classification d’images et de vidéos : Supervised Multi-layer Dictionary learning for image and video classification.” 2016. Web. 13 Aug 2020.

Vancouver:

Chan wai tim S. Apprentissage supervisé d’une représentation multi-couches à base de dictionnaires pour la classification d’images et de vidéos : Supervised Multi-layer Dictionary learning for image and video classification. [Internet] [Doctoral dissertation]. Université Grenoble Alpes (ComUE); 2016. [cited 2020 Aug 13]. Available from: http://www.theses.fr/2016GREAT089.

Council of Science Editors:

Chan wai tim S. Apprentissage supervisé d’une représentation multi-couches à base de dictionnaires pour la classification d’images et de vidéos : Supervised Multi-layer Dictionary learning for image and video classification. [Doctoral Dissertation]. Université Grenoble Alpes (ComUE); 2016. Available from: http://www.theses.fr/2016GREAT089

11. Ech-Choudany, Youssef. Analyse des signaux non-stationnaires à l’aide d’une nouvelle démarche de classification : application à l’identification de l’endommagement de matériaux composites par émission acoustique et à la détection de la crise d’épilepsie par EEG : Non-stationary signal analysis using a new classification approach : application to damage identification in composites materials using acoustic emission and to the epileptic seizure detection in EEGs.

Degree: Docteur es, ATS - Automatique et Traitement de Signal, 2018, Reims; ENSA – École National des Sciences Appliquées -Université Mohamed Premier

Proposé dans le cadre d’une triple collaboration entre le Centre de Recherche en Science et Technologie de l'Information et de la Communication (CReSTIC) de l'Université… (more)

Subjects/Keywords: Emission acoustique; Eeg; Endommagement; Temps-Fréquence; Classification; Signal; Acoustic emission; Eeg; Damage events; Time-Frequency; Classification; Signal; 620.118

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APA (6th Edition):

Ech-Choudany, Y. (2018). Analyse des signaux non-stationnaires à l’aide d’une nouvelle démarche de classification : application à l’identification de l’endommagement de matériaux composites par émission acoustique et à la détection de la crise d’épilepsie par EEG : Non-stationary signal analysis using a new classification approach : application to damage identification in composites materials using acoustic emission and to the epileptic seizure detection in EEGs. (Doctoral Dissertation). Reims; ENSA – École National des Sciences Appliquées -Université Mohamed Premier. Retrieved from http://www.theses.fr/2018REIMS020

Chicago Manual of Style (16th Edition):

Ech-Choudany, Youssef. “Analyse des signaux non-stationnaires à l’aide d’une nouvelle démarche de classification : application à l’identification de l’endommagement de matériaux composites par émission acoustique et à la détection de la crise d’épilepsie par EEG : Non-stationary signal analysis using a new classification approach : application to damage identification in composites materials using acoustic emission and to the epileptic seizure detection in EEGs.” 2018. Doctoral Dissertation, Reims; ENSA – École National des Sciences Appliquées -Université Mohamed Premier. Accessed August 13, 2020. http://www.theses.fr/2018REIMS020.

MLA Handbook (7th Edition):

Ech-Choudany, Youssef. “Analyse des signaux non-stationnaires à l’aide d’une nouvelle démarche de classification : application à l’identification de l’endommagement de matériaux composites par émission acoustique et à la détection de la crise d’épilepsie par EEG : Non-stationary signal analysis using a new classification approach : application to damage identification in composites materials using acoustic emission and to the epileptic seizure detection in EEGs.” 2018. Web. 13 Aug 2020.

Vancouver:

Ech-Choudany Y. Analyse des signaux non-stationnaires à l’aide d’une nouvelle démarche de classification : application à l’identification de l’endommagement de matériaux composites par émission acoustique et à la détection de la crise d’épilepsie par EEG : Non-stationary signal analysis using a new classification approach : application to damage identification in composites materials using acoustic emission and to the epileptic seizure detection in EEGs. [Internet] [Doctoral dissertation]. Reims; ENSA – École National des Sciences Appliquées -Université Mohamed Premier; 2018. [cited 2020 Aug 13]. Available from: http://www.theses.fr/2018REIMS020.

Council of Science Editors:

Ech-Choudany Y. Analyse des signaux non-stationnaires à l’aide d’une nouvelle démarche de classification : application à l’identification de l’endommagement de matériaux composites par émission acoustique et à la détection de la crise d’épilepsie par EEG : Non-stationary signal analysis using a new classification approach : application to damage identification in composites materials using acoustic emission and to the epileptic seizure detection in EEGs. [Doctoral Dissertation]. Reims; ENSA – École National des Sciences Appliquées -Université Mohamed Premier; 2018. Available from: http://www.theses.fr/2018REIMS020


Dalhousie University

12. Binder, Carolyn. Using an Aural Classifier to Discriminate Cetacean Vocalizations.

Degree: MS, Department of Physics & Atmospheric Science, 2012, Dalhousie University

 To positively identify marine mammals using passive acoustics, large volumes of data are often collected that need to be processed by a trained analyst. To… (more)

Subjects/Keywords: Marine mammals; Underwater acoustics; Marine bioacoustics; Aural classification; Perceptual signal features; Automatic detection and classification

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APA (6th Edition):

Binder, C. (2012). Using an Aural Classifier to Discriminate Cetacean Vocalizations. (Masters Thesis). Dalhousie University. Retrieved from http://hdl.handle.net/10222/14607

Chicago Manual of Style (16th Edition):

Binder, Carolyn. “Using an Aural Classifier to Discriminate Cetacean Vocalizations.” 2012. Masters Thesis, Dalhousie University. Accessed August 13, 2020. http://hdl.handle.net/10222/14607.

MLA Handbook (7th Edition):

Binder, Carolyn. “Using an Aural Classifier to Discriminate Cetacean Vocalizations.” 2012. Web. 13 Aug 2020.

Vancouver:

Binder C. Using an Aural Classifier to Discriminate Cetacean Vocalizations. [Internet] [Masters thesis]. Dalhousie University; 2012. [cited 2020 Aug 13]. Available from: http://hdl.handle.net/10222/14607.

Council of Science Editors:

Binder C. Using an Aural Classifier to Discriminate Cetacean Vocalizations. [Masters Thesis]. Dalhousie University; 2012. Available from: http://hdl.handle.net/10222/14607


Delft University of Technology

13. Montesinos García, Lucas (author). Audio-visual authentication for mobile devices.

Degree: 2018, Delft University of Technology

Authentication is becoming an increasingly important application in the connected world and is driven by the growing use of mobile and IoT devices that use… (more)

Subjects/Keywords: Authentication; Classification; Machine Learning; Computer Vision; Signal Detection Theory; Audio Classification; Verification

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APA (6th Edition):

Montesinos García, L. (. (2018). Audio-visual authentication for mobile devices. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:0e8a2a7f-d188-47c9-9d7c-5721ac3056a1

Chicago Manual of Style (16th Edition):

Montesinos García, Lucas (author). “Audio-visual authentication for mobile devices.” 2018. Masters Thesis, Delft University of Technology. Accessed August 13, 2020. http://resolver.tudelft.nl/uuid:0e8a2a7f-d188-47c9-9d7c-5721ac3056a1.

MLA Handbook (7th Edition):

Montesinos García, Lucas (author). “Audio-visual authentication for mobile devices.” 2018. Web. 13 Aug 2020.

Vancouver:

Montesinos García L(. Audio-visual authentication for mobile devices. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2020 Aug 13]. Available from: http://resolver.tudelft.nl/uuid:0e8a2a7f-d188-47c9-9d7c-5721ac3056a1.

Council of Science Editors:

Montesinos García L(. Audio-visual authentication for mobile devices. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:0e8a2a7f-d188-47c9-9d7c-5721ac3056a1


University of California – Irvine

14. Szymanska, Agnieszka Anna Fielder. Action Potentials and Waves: A Short Story on Electrophysiological Signal Processing.

Degree: Biomedical Engineering, 2017, University of California – Irvine

 Electrophysiological signal processing is a broad, complex and growing field. Universally, the first steps of any signal analysis are detection and classification. Here we present… (more)

Subjects/Keywords: Biomedical engineering; Neurosciences; Anesthesia; Classification; Detection; MUA; Neuroengineering; Signal Processing

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Szymanska, A. A. F. (2017). Action Potentials and Waves: A Short Story on Electrophysiological Signal Processing. (Thesis). University of California – Irvine. Retrieved from http://www.escholarship.org/uc/item/98t9n6c4

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Szymanska, Agnieszka Anna Fielder. “Action Potentials and Waves: A Short Story on Electrophysiological Signal Processing.” 2017. Thesis, University of California – Irvine. Accessed August 13, 2020. http://www.escholarship.org/uc/item/98t9n6c4.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Szymanska, Agnieszka Anna Fielder. “Action Potentials and Waves: A Short Story on Electrophysiological Signal Processing.” 2017. Web. 13 Aug 2020.

Vancouver:

Szymanska AAF. Action Potentials and Waves: A Short Story on Electrophysiological Signal Processing. [Internet] [Thesis]. University of California – Irvine; 2017. [cited 2020 Aug 13]. Available from: http://www.escholarship.org/uc/item/98t9n6c4.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Szymanska AAF. Action Potentials and Waves: A Short Story on Electrophysiological Signal Processing. [Thesis]. University of California – Irvine; 2017. Available from: http://www.escholarship.org/uc/item/98t9n6c4

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Stellenbosch University

15. Uys, Pieter Johannes. Image classification from EEG Brain Signals using machine learning and deep learning techniques.

Degree: MEng, Mechanical and Mechatronic Engineering, 2019, Stellenbosch University

ENGLISH ABSTRACT: Please refer to full text for abstract

AFRIKAANSE OPSOMMING: Raadpleeg teks vir opsomming

Advisors/Committee Members: Van den Heever, Dawie, Stellenbosch University. Faculty of Engineering. Dept. of Mechanical and Mechatronic Engineering..

Subjects/Keywords: Brain signal classification; EEG; Machine learning; Learning systems; UCTD

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APA (6th Edition):

Uys, P. J. (2019). Image classification from EEG Brain Signals using machine learning and deep learning techniques. (Thesis). Stellenbosch University. Retrieved from http://hdl.handle.net/10019.1/107299

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Uys, Pieter Johannes. “Image classification from EEG Brain Signals using machine learning and deep learning techniques.” 2019. Thesis, Stellenbosch University. Accessed August 13, 2020. http://hdl.handle.net/10019.1/107299.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Uys, Pieter Johannes. “Image classification from EEG Brain Signals using machine learning and deep learning techniques.” 2019. Web. 13 Aug 2020.

Vancouver:

Uys PJ. Image classification from EEG Brain Signals using machine learning and deep learning techniques. [Internet] [Thesis]. Stellenbosch University; 2019. [cited 2020 Aug 13]. Available from: http://hdl.handle.net/10019.1/107299.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Uys PJ. Image classification from EEG Brain Signals using machine learning and deep learning techniques. [Thesis]. Stellenbosch University; 2019. Available from: http://hdl.handle.net/10019.1/107299

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Penn State University

16. Srinivas, Umamahesh. Discriminative models for robust image classification.

Degree: 2013, Penn State University

 A variety of real-world tasks involve the classification of images into pre-determined categories. Designing image classification algorithms that exhibit robustness to acquisition noise and image… (more)

Subjects/Keywords: Robust image classification; image processing; graphical models; sparse signal representations.

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APA (6th Edition):

Srinivas, U. (2013). Discriminative models for robust image classification. (Thesis). Penn State University. Retrieved from https://submit-etda.libraries.psu.edu/catalog/19014

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Srinivas, Umamahesh. “Discriminative models for robust image classification.” 2013. Thesis, Penn State University. Accessed August 13, 2020. https://submit-etda.libraries.psu.edu/catalog/19014.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Srinivas, Umamahesh. “Discriminative models for robust image classification.” 2013. Web. 13 Aug 2020.

Vancouver:

Srinivas U. Discriminative models for robust image classification. [Internet] [Thesis]. Penn State University; 2013. [cited 2020 Aug 13]. Available from: https://submit-etda.libraries.psu.edu/catalog/19014.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Srinivas U. Discriminative models for robust image classification. [Thesis]. Penn State University; 2013. Available from: https://submit-etda.libraries.psu.edu/catalog/19014

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Wright State University

17. Like, Eric C. Non-Cooperative Modulation Recognition Via Exploitation of Cyclic Statistics.

Degree: MSEgr, Electrical Engineering, 2007, Wright State University

 This research proposes and evaluates a feature based modulation classification system designed to discriminate between AM, BFSK, OFDM, DS-CDMA, 4-ASK, 8-ASK, BPSK, QPSK, 8-PSK, 16-… (more)

Subjects/Keywords: Modulation Recognition; Cyclostationarity; Signal Classification; Spectral Correlation; Cognitive Radio

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APA (6th Edition):

Like, E. C. (2007). Non-Cooperative Modulation Recognition Via Exploitation of Cyclic Statistics. (Masters Thesis). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1197649202

Chicago Manual of Style (16th Edition):

Like, Eric C. “Non-Cooperative Modulation Recognition Via Exploitation of Cyclic Statistics.” 2007. Masters Thesis, Wright State University. Accessed August 13, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=wright1197649202.

MLA Handbook (7th Edition):

Like, Eric C. “Non-Cooperative Modulation Recognition Via Exploitation of Cyclic Statistics.” 2007. Web. 13 Aug 2020.

Vancouver:

Like EC. Non-Cooperative Modulation Recognition Via Exploitation of Cyclic Statistics. [Internet] [Masters thesis]. Wright State University; 2007. [cited 2020 Aug 13]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1197649202.

Council of Science Editors:

Like EC. Non-Cooperative Modulation Recognition Via Exploitation of Cyclic Statistics. [Masters Thesis]. Wright State University; 2007. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1197649202


NSYSU

18. Chen, Hsing-Feng. Application of Hybrid Antennas in Normalized Site Attenuation Measurements and An Improved Method for Free-space Antenna Factor Measurement.

Degree: PhD, Electrical Engineering, 2010, NSYSU

 This thesis first discusses the ground plane effects of a test site on the antenna factors (AFs) of hybrid antenna (biconical log-periodic dipole array). Meanwhile,… (more)

Subjects/Keywords: normalized site attenuation; antenna factor; multiple signal classification

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chen, H. (2010). Application of Hybrid Antennas in Normalized Site Attenuation Measurements and An Improved Method for Free-space Antenna Factor Measurement. (Doctoral Dissertation). NSYSU. Retrieved from http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0118110-211617

Chicago Manual of Style (16th Edition):

Chen, Hsing-Feng. “Application of Hybrid Antennas in Normalized Site Attenuation Measurements and An Improved Method for Free-space Antenna Factor Measurement.” 2010. Doctoral Dissertation, NSYSU. Accessed August 13, 2020. http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0118110-211617.

MLA Handbook (7th Edition):

Chen, Hsing-Feng. “Application of Hybrid Antennas in Normalized Site Attenuation Measurements and An Improved Method for Free-space Antenna Factor Measurement.” 2010. Web. 13 Aug 2020.

Vancouver:

Chen H. Application of Hybrid Antennas in Normalized Site Attenuation Measurements and An Improved Method for Free-space Antenna Factor Measurement. [Internet] [Doctoral dissertation]. NSYSU; 2010. [cited 2020 Aug 13]. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0118110-211617.

Council of Science Editors:

Chen H. Application of Hybrid Antennas in Normalized Site Attenuation Measurements and An Improved Method for Free-space Antenna Factor Measurement. [Doctoral Dissertation]. NSYSU; 2010. Available from: http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0118110-211617


Virginia Tech

19. Marballie, Gladstone Washington. Symbol Timing and Coarse Classification of Phase Modulated Signals on a Standalone SDR Platform.

Degree: MS, Electrical and Computer Engineering, 2010, Virginia Tech

 The Universal Classifier Synchronizer (UCS) is a Cognitive Radio system/sensor that can detect, classify, and extract the relevant parameters from a received signal to establish… (more)

Subjects/Keywords: FPGA; Signal Classification; Symbol Timing; DSP; SDR; Cognitive Radio

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APA (6th Edition):

Marballie, G. W. (2010). Symbol Timing and Coarse Classification of Phase Modulated Signals on a Standalone SDR Platform. (Masters Thesis). Virginia Tech. Retrieved from http://hdl.handle.net/10919/35409

Chicago Manual of Style (16th Edition):

Marballie, Gladstone Washington. “Symbol Timing and Coarse Classification of Phase Modulated Signals on a Standalone SDR Platform.” 2010. Masters Thesis, Virginia Tech. Accessed August 13, 2020. http://hdl.handle.net/10919/35409.

MLA Handbook (7th Edition):

Marballie, Gladstone Washington. “Symbol Timing and Coarse Classification of Phase Modulated Signals on a Standalone SDR Platform.” 2010. Web. 13 Aug 2020.

Vancouver:

Marballie GW. Symbol Timing and Coarse Classification of Phase Modulated Signals on a Standalone SDR Platform. [Internet] [Masters thesis]. Virginia Tech; 2010. [cited 2020 Aug 13]. Available from: http://hdl.handle.net/10919/35409.

Council of Science Editors:

Marballie GW. Symbol Timing and Coarse Classification of Phase Modulated Signals on a Standalone SDR Platform. [Masters Thesis]. Virginia Tech; 2010. Available from: http://hdl.handle.net/10919/35409


Virginia Tech

20. Headley, William C. Spectrum Sensing in the Presence of Channel and Tx/Rx Impairments.

Degree: PhD, Electrical and Computer Engineering, 2015, Virginia Tech

 The task of spectrum sensing, defined here to consist of signal detection, signal parameter estimation, and signal identification, is a critically important task in a… (more)

Subjects/Keywords: spectrum sensing; signal parameter estimation; modulation classification; collaborative sensing

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APA (6th Edition):

Headley, W. C. (2015). Spectrum Sensing in the Presence of Channel and Tx/Rx Impairments. (Doctoral Dissertation). Virginia Tech. Retrieved from http://hdl.handle.net/10919/52915

Chicago Manual of Style (16th Edition):

Headley, William C. “Spectrum Sensing in the Presence of Channel and Tx/Rx Impairments.” 2015. Doctoral Dissertation, Virginia Tech. Accessed August 13, 2020. http://hdl.handle.net/10919/52915.

MLA Handbook (7th Edition):

Headley, William C. “Spectrum Sensing in the Presence of Channel and Tx/Rx Impairments.” 2015. Web. 13 Aug 2020.

Vancouver:

Headley WC. Spectrum Sensing in the Presence of Channel and Tx/Rx Impairments. [Internet] [Doctoral dissertation]. Virginia Tech; 2015. [cited 2020 Aug 13]. Available from: http://hdl.handle.net/10919/52915.

Council of Science Editors:

Headley WC. Spectrum Sensing in the Presence of Channel and Tx/Rx Impairments. [Doctoral Dissertation]. Virginia Tech; 2015. Available from: http://hdl.handle.net/10919/52915


University of Toronto

21. Hassan, Ahnaf Rashik. Developing a System for High-Resolution Detection of Driver Drowsiness Using Physiological Signals.

Degree: 2018, University of Toronto

Background: This research aims to develop a high-resolution, reliable, and efficient drowsiness detection system. Existing systems for detecting drowsiness are of low-resolution, expensive, dependent on… (more)

Subjects/Keywords: Biomedical Signal Processing; Classification; Drowsiness; EEG; Machine Learning; Road Safety; 0541

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APA (6th Edition):

Hassan, A. R. (2018). Developing a System for High-Resolution Detection of Driver Drowsiness Using Physiological Signals. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/91556

Chicago Manual of Style (16th Edition):

Hassan, Ahnaf Rashik. “Developing a System for High-Resolution Detection of Driver Drowsiness Using Physiological Signals.” 2018. Masters Thesis, University of Toronto. Accessed August 13, 2020. http://hdl.handle.net/1807/91556.

MLA Handbook (7th Edition):

Hassan, Ahnaf Rashik. “Developing a System for High-Resolution Detection of Driver Drowsiness Using Physiological Signals.” 2018. Web. 13 Aug 2020.

Vancouver:

Hassan AR. Developing a System for High-Resolution Detection of Driver Drowsiness Using Physiological Signals. [Internet] [Masters thesis]. University of Toronto; 2018. [cited 2020 Aug 13]. Available from: http://hdl.handle.net/1807/91556.

Council of Science Editors:

Hassan AR. Developing a System for High-Resolution Detection of Driver Drowsiness Using Physiological Signals. [Masters Thesis]. University of Toronto; 2018. Available from: http://hdl.handle.net/1807/91556

22. Anu Sabarish R; Dr. Tessamma Thomas. Genomic Signal Processing Methods for Detection of Copy Number Variation from Array CGH Data and Phylogenetic Classification using Protein Sequences.

Degree: 2017, Cochin University of Science and Technology

Subjects/Keywords: Genomic Signal Processing; Phylogenetic Classification

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APA (6th Edition):

Thomas, A. S. R. D. T. (2017). Genomic Signal Processing Methods for Detection of Copy Number Variation from Array CGH Data and Phylogenetic Classification using Protein Sequences. (Thesis). Cochin University of Science and Technology. Retrieved from http://dyuthi.cusat.ac.in/purl/5422

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Thomas, Anu Sabarish R; Dr. Tessamma. “Genomic Signal Processing Methods for Detection of Copy Number Variation from Array CGH Data and Phylogenetic Classification using Protein Sequences.” 2017. Thesis, Cochin University of Science and Technology. Accessed August 13, 2020. http://dyuthi.cusat.ac.in/purl/5422.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Thomas, Anu Sabarish R; Dr. Tessamma. “Genomic Signal Processing Methods for Detection of Copy Number Variation from Array CGH Data and Phylogenetic Classification using Protein Sequences.” 2017. Web. 13 Aug 2020.

Vancouver:

Thomas ASRDT. Genomic Signal Processing Methods for Detection of Copy Number Variation from Array CGH Data and Phylogenetic Classification using Protein Sequences. [Internet] [Thesis]. Cochin University of Science and Technology; 2017. [cited 2020 Aug 13]. Available from: http://dyuthi.cusat.ac.in/purl/5422.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Thomas ASRDT. Genomic Signal Processing Methods for Detection of Copy Number Variation from Array CGH Data and Phylogenetic Classification using Protein Sequences. [Thesis]. Cochin University of Science and Technology; 2017. Available from: http://dyuthi.cusat.ac.in/purl/5422

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Houston

23. Aroua, Nesrine. Using Wireless Dry EEG System to Detect Mental Workload during Mental Arithmetic.

Degree: MS, Biomedical Engineering, 2016, University of Houston

 Mental workload, the amount of cognitive resources invested during a task, is a crucial metric for performance. Determining the performance of an individual aids in… (more)

Subjects/Keywords: EEG; Mental workload; Electroencephalography (EEG); Biomedical signal processing; Classification

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APA (6th Edition):

Aroua, N. (2016). Using Wireless Dry EEG System to Detect Mental Workload during Mental Arithmetic. (Masters Thesis). University of Houston. Retrieved from http://hdl.handle.net/10657/3219

Chicago Manual of Style (16th Edition):

Aroua, Nesrine. “Using Wireless Dry EEG System to Detect Mental Workload during Mental Arithmetic.” 2016. Masters Thesis, University of Houston. Accessed August 13, 2020. http://hdl.handle.net/10657/3219.

MLA Handbook (7th Edition):

Aroua, Nesrine. “Using Wireless Dry EEG System to Detect Mental Workload during Mental Arithmetic.” 2016. Web. 13 Aug 2020.

Vancouver:

Aroua N. Using Wireless Dry EEG System to Detect Mental Workload during Mental Arithmetic. [Internet] [Masters thesis]. University of Houston; 2016. [cited 2020 Aug 13]. Available from: http://hdl.handle.net/10657/3219.

Council of Science Editors:

Aroua N. Using Wireless Dry EEG System to Detect Mental Workload during Mental Arithmetic. [Masters Thesis]. University of Houston; 2016. Available from: http://hdl.handle.net/10657/3219


Linköping University

24. Tapper, Gustav. Extraction of DTM from Satellite Images Using Neural Networks.

Degree: Computer Vision, 2016, Linköping University

  This thesis presents a way to generate a Digital Terrain Model (dtm) from a Digital Surface Model (dsm) and multi spectral images (including the… (more)

Subjects/Keywords: DTM; DSM; classification; neural networks; satellite images; Signal Processing; Signalbehandling

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APA (6th Edition):

Tapper, G. (2016). Extraction of DTM from Satellite Images Using Neural Networks. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-133337

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Tapper, Gustav. “Extraction of DTM from Satellite Images Using Neural Networks.” 2016. Thesis, Linköping University. Accessed August 13, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-133337.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Tapper, Gustav. “Extraction of DTM from Satellite Images Using Neural Networks.” 2016. Web. 13 Aug 2020.

Vancouver:

Tapper G. Extraction of DTM from Satellite Images Using Neural Networks. [Internet] [Thesis]. Linköping University; 2016. [cited 2020 Aug 13]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-133337.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tapper G. Extraction of DTM from Satellite Images Using Neural Networks. [Thesis]. Linköping University; 2016. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-133337

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

25. Mestre-Quereda, Alejandro. Advanced Processing Techniques and Applications of Synthetic Aperture Radar Interferometry .

Degree: 2019, University of Alicante

 Synthetic Aperture Radar interferometry (InSAR) is a powerful and established technique, which is based on exploiting the phase difference between pairs of SAR images, and… (more)

Subjects/Keywords: SAR Interferometry; Polarimetry; Signal Processing; Image Classification; Machine Learning

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APA (6th Edition):

Mestre-Quereda, A. (2019). Advanced Processing Techniques and Applications of Synthetic Aperture Radar Interferometry . (Thesis). University of Alicante. Retrieved from http://hdl.handle.net/10045/101167

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mestre-Quereda, Alejandro. “Advanced Processing Techniques and Applications of Synthetic Aperture Radar Interferometry .” 2019. Thesis, University of Alicante. Accessed August 13, 2020. http://hdl.handle.net/10045/101167.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mestre-Quereda, Alejandro. “Advanced Processing Techniques and Applications of Synthetic Aperture Radar Interferometry .” 2019. Web. 13 Aug 2020.

Vancouver:

Mestre-Quereda A. Advanced Processing Techniques and Applications of Synthetic Aperture Radar Interferometry . [Internet] [Thesis]. University of Alicante; 2019. [cited 2020 Aug 13]. Available from: http://hdl.handle.net/10045/101167.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mestre-Quereda A. Advanced Processing Techniques and Applications of Synthetic Aperture Radar Interferometry . [Thesis]. University of Alicante; 2019. Available from: http://hdl.handle.net/10045/101167

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

26. Moger, Michael. Classification of Arbitrary Motion into a Canonical Basis.

Degree: MS, 2018, University of New Hampshire

 The Empatica E4 wristwatch utilizes four sensors to capture medical data from its user - an accelerometer, a plethysmograph, an electro-dermal activity sensor, and an… (more)

Subjects/Keywords: Empatica; Machine learning; Matching pursuit; Signal classification; Singular value decomposition

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APA (6th Edition):

Moger, M. (2018). Classification of Arbitrary Motion into a Canonical Basis. (Thesis). University of New Hampshire. Retrieved from https://scholars.unh.edu/thesis/1258

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Moger, Michael. “Classification of Arbitrary Motion into a Canonical Basis.” 2018. Thesis, University of New Hampshire. Accessed August 13, 2020. https://scholars.unh.edu/thesis/1258.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Moger, Michael. “Classification of Arbitrary Motion into a Canonical Basis.” 2018. Web. 13 Aug 2020.

Vancouver:

Moger M. Classification of Arbitrary Motion into a Canonical Basis. [Internet] [Thesis]. University of New Hampshire; 2018. [cited 2020 Aug 13]. Available from: https://scholars.unh.edu/thesis/1258.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Moger M. Classification of Arbitrary Motion into a Canonical Basis. [Thesis]. University of New Hampshire; 2018. Available from: https://scholars.unh.edu/thesis/1258

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Linköping University

27. Pop, David. Classification of Heart Views in Ultrasound Images.

Degree: Computer Vision, 2020, Linköping University

  In today’s society, we experience an increasing challenge to provide healthcare to everyone in need due to the increasing number of patients and the… (more)

Subjects/Keywords: AI; deep learning; echocardiography; image classification; Signal Processing; Signalbehandling

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APA (6th Edition):

Pop, D. (2020). Classification of Heart Views in Ultrasound Images. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-165276

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Pop, David. “Classification of Heart Views in Ultrasound Images.” 2020. Thesis, Linköping University. Accessed August 13, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-165276.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Pop, David. “Classification of Heart Views in Ultrasound Images.” 2020. Web. 13 Aug 2020.

Vancouver:

Pop D. Classification of Heart Views in Ultrasound Images. [Internet] [Thesis]. Linköping University; 2020. [cited 2020 Aug 13]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-165276.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Pop D. Classification of Heart Views in Ultrasound Images. [Thesis]. Linköping University; 2020. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-165276

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

28. Marchese, Andrew. Data Analysis Methods using Persistence Diagrams.

Degree: 2017, University of Tennessee – Knoxville

 In recent years, persistent homology techniques have been used to study data and dynamical systems. Using these techniques, information about the shape and geometry of… (more)

Subjects/Keywords: Machine Learning; Data Science; Signal Processing; Statistics; Classification; Clustering; Statistical Models

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Marchese, A. (2017). Data Analysis Methods using Persistence Diagrams. (Doctoral Dissertation). University of Tennessee – Knoxville. Retrieved from https://trace.tennessee.edu/utk_graddiss/4700

Chicago Manual of Style (16th Edition):

Marchese, Andrew. “Data Analysis Methods using Persistence Diagrams.” 2017. Doctoral Dissertation, University of Tennessee – Knoxville. Accessed August 13, 2020. https://trace.tennessee.edu/utk_graddiss/4700.

MLA Handbook (7th Edition):

Marchese, Andrew. “Data Analysis Methods using Persistence Diagrams.” 2017. Web. 13 Aug 2020.

Vancouver:

Marchese A. Data Analysis Methods using Persistence Diagrams. [Internet] [Doctoral dissertation]. University of Tennessee – Knoxville; 2017. [cited 2020 Aug 13]. Available from: https://trace.tennessee.edu/utk_graddiss/4700.

Council of Science Editors:

Marchese A. Data Analysis Methods using Persistence Diagrams. [Doctoral Dissertation]. University of Tennessee – Knoxville; 2017. Available from: https://trace.tennessee.edu/utk_graddiss/4700

29. Akaydın, Sümeye Nur. Radar video görüntülerinde karasal alanların belirlenmesi: Determination of land regions in radar video image.

Degree: Mühendislik Fakültesi, 2018, University of Ankara

 Radar sistemlerinde hedefin tespit edilme olasılığını azaltan etmenlerin azaltılması önemli bir konudur. Kıyı sınırlarının güvenliğinin sağlanması veya gemi takibi yapılması gibi uygulamalarda sadece takibi yapılan… (more)

Subjects/Keywords: Radar sinyal işleme; Kara sınıflandırma; Radar signal processing; Land classification

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Akaydın, S. N. (2018). Radar video görüntülerinde karasal alanların belirlenmesi: Determination of land regions in radar video image. (Masters Thesis). University of Ankara. Retrieved from http://hdl.handle.net/20.500.12575/69283

Chicago Manual of Style (16th Edition):

Akaydın, Sümeye Nur. “Radar video görüntülerinde karasal alanların belirlenmesi: Determination of land regions in radar video image.” 2018. Masters Thesis, University of Ankara. Accessed August 13, 2020. http://hdl.handle.net/20.500.12575/69283.

MLA Handbook (7th Edition):

Akaydın, Sümeye Nur. “Radar video görüntülerinde karasal alanların belirlenmesi: Determination of land regions in radar video image.” 2018. Web. 13 Aug 2020.

Vancouver:

Akaydın SN. Radar video görüntülerinde karasal alanların belirlenmesi: Determination of land regions in radar video image. [Internet] [Masters thesis]. University of Ankara; 2018. [cited 2020 Aug 13]. Available from: http://hdl.handle.net/20.500.12575/69283.

Council of Science Editors:

Akaydın SN. Radar video görüntülerinde karasal alanların belirlenmesi: Determination of land regions in radar video image. [Masters Thesis]. University of Ankara; 2018. Available from: http://hdl.handle.net/20.500.12575/69283


University of Pennsylvania

30. Moulton, Jeannie L. Enhanced High-Resolution Imaging through Multiple-Frequency Coarray Augmentation.

Degree: 2010, University of Pennsylvania

 In imaging, much attention is paid to increasing the resolution capabilities of a system. Increasing resolution allows for high-accuracy source location and the ability to… (more)

Subjects/Keywords: High-resolution imaging; Direction-of-arrival estimation; Wideband imaging; Coarray; Virtual arrays; Multiple Signal Classification; Signal Processing

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Moulton, J. L. (2010). Enhanced High-Resolution Imaging through Multiple-Frequency Coarray Augmentation. (Thesis). University of Pennsylvania. Retrieved from https://repository.upenn.edu/edissertations/240

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Moulton, Jeannie L. “Enhanced High-Resolution Imaging through Multiple-Frequency Coarray Augmentation.” 2010. Thesis, University of Pennsylvania. Accessed August 13, 2020. https://repository.upenn.edu/edissertations/240.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Moulton, Jeannie L. “Enhanced High-Resolution Imaging through Multiple-Frequency Coarray Augmentation.” 2010. Web. 13 Aug 2020.

Vancouver:

Moulton JL. Enhanced High-Resolution Imaging through Multiple-Frequency Coarray Augmentation. [Internet] [Thesis]. University of Pennsylvania; 2010. [cited 2020 Aug 13]. Available from: https://repository.upenn.edu/edissertations/240.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Moulton JL. Enhanced High-Resolution Imaging through Multiple-Frequency Coarray Augmentation. [Thesis]. University of Pennsylvania; 2010. Available from: https://repository.upenn.edu/edissertations/240

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

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