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You searched for subject:(Gaussian mixtures). Showing records 1 – 18 of 18 total matches.

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University of Cincinnati

1. Zhao, Nan. Accelerated T1 and T2 Parameter Mapping and Data Denoising Methods for 3D Quantitative MRI.

Degree: PhD, Arts and Sciences: Physics, 2020, University of Cincinnati

 Fast imaging has long been a key direction of magnetic resonance imaging (MRI) research. Rapid imaging technology can not only shorten the measurement time, reducing… (more)

Subjects/Keywords: Radiology; fast imaging; DESPOT1T2 mapping; Quantitative MRI; multichannel denoising; Gaussian scale mixtures; Bayesian estimation

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APA (6th Edition):

Zhao, N. (2020). Accelerated T1 and T2 Parameter Mapping and Data Denoising Methods for 3D Quantitative MRI. (Doctoral Dissertation). University of Cincinnati. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=ucin1613748540796138

Chicago Manual of Style (16th Edition):

Zhao, Nan. “Accelerated T1 and T2 Parameter Mapping and Data Denoising Methods for 3D Quantitative MRI.” 2020. Doctoral Dissertation, University of Cincinnati. Accessed April 22, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1613748540796138.

MLA Handbook (7th Edition):

Zhao, Nan. “Accelerated T1 and T2 Parameter Mapping and Data Denoising Methods for 3D Quantitative MRI.” 2020. Web. 22 Apr 2021.

Vancouver:

Zhao N. Accelerated T1 and T2 Parameter Mapping and Data Denoising Methods for 3D Quantitative MRI. [Internet] [Doctoral dissertation]. University of Cincinnati; 2020. [cited 2021 Apr 22]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1613748540796138.

Council of Science Editors:

Zhao N. Accelerated T1 and T2 Parameter Mapping and Data Denoising Methods for 3D Quantitative MRI. [Doctoral Dissertation]. University of Cincinnati; 2020. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=ucin1613748540796138

2. Fernandes maligo, Artur otavio. Unsupervised Gaussian mixture models for the classification of outdoor environments using 3D terrestrial lidar data : Modèles de mélange gaussien sans surveillance pour la classification des environnements extérieurs en utilisant des données 3D de lidar terrestre.

Degree: Docteur es, Robotique, 2016, Toulouse, INSA

Le traitement de nuages de points 3D de lidars permet aux robots mobiles autonomes terrestres de construire des modèles sémantiques de l'environnement extérieur dans lequel… (more)

Subjects/Keywords: Classification non-supervisée; Mélange de gaussiennes; Données 3D Lidar; Gaussian mixtures; Lidar point-clouds; Unsupervised classification; 629.8

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APA (6th Edition):

Fernandes maligo, A. o. (2016). Unsupervised Gaussian mixture models for the classification of outdoor environments using 3D terrestrial lidar data : Modèles de mélange gaussien sans surveillance pour la classification des environnements extérieurs en utilisant des données 3D de lidar terrestre. (Doctoral Dissertation). Toulouse, INSA. Retrieved from http://www.theses.fr/2016ISAT0053

Chicago Manual of Style (16th Edition):

Fernandes maligo, Artur otavio. “Unsupervised Gaussian mixture models for the classification of outdoor environments using 3D terrestrial lidar data : Modèles de mélange gaussien sans surveillance pour la classification des environnements extérieurs en utilisant des données 3D de lidar terrestre.” 2016. Doctoral Dissertation, Toulouse, INSA. Accessed April 22, 2021. http://www.theses.fr/2016ISAT0053.

MLA Handbook (7th Edition):

Fernandes maligo, Artur otavio. “Unsupervised Gaussian mixture models for the classification of outdoor environments using 3D terrestrial lidar data : Modèles de mélange gaussien sans surveillance pour la classification des environnements extérieurs en utilisant des données 3D de lidar terrestre.” 2016. Web. 22 Apr 2021.

Vancouver:

Fernandes maligo Ao. Unsupervised Gaussian mixture models for the classification of outdoor environments using 3D terrestrial lidar data : Modèles de mélange gaussien sans surveillance pour la classification des environnements extérieurs en utilisant des données 3D de lidar terrestre. [Internet] [Doctoral dissertation]. Toulouse, INSA; 2016. [cited 2021 Apr 22]. Available from: http://www.theses.fr/2016ISAT0053.

Council of Science Editors:

Fernandes maligo Ao. Unsupervised Gaussian mixture models for the classification of outdoor environments using 3D terrestrial lidar data : Modèles de mélange gaussien sans surveillance pour la classification des environnements extérieurs en utilisant des données 3D de lidar terrestre. [Doctoral Dissertation]. Toulouse, INSA; 2016. Available from: http://www.theses.fr/2016ISAT0053

3. Sebbar, Mehdi. On unsupervised learning in high dimension : Sur l'apprentissage non supervisé en haute dimension.

Degree: Docteur es, Mathématiques appliquées, 2017, Université Paris-Saclay (ComUE)

 Dans ce mémoire de thèse, nous abordons deux thèmes, le clustering en haute dimension d'une part et l'estimation de densités de mélange d'autre part. Le… (more)

Subjects/Keywords: Clustering; Agrégation; Grande dimension; Estimation de densité; Mélange de gaussiennes; Gaussian mixtures; Clustering; High dimension; Density estimation; Aggregation; 519; 62

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APA (6th Edition):

Sebbar, M. (2017). On unsupervised learning in high dimension : Sur l'apprentissage non supervisé en haute dimension. (Doctoral Dissertation). Université Paris-Saclay (ComUE). Retrieved from http://www.theses.fr/2017SACLG003

Chicago Manual of Style (16th Edition):

Sebbar, Mehdi. “On unsupervised learning in high dimension : Sur l'apprentissage non supervisé en haute dimension.” 2017. Doctoral Dissertation, Université Paris-Saclay (ComUE). Accessed April 22, 2021. http://www.theses.fr/2017SACLG003.

MLA Handbook (7th Edition):

Sebbar, Mehdi. “On unsupervised learning in high dimension : Sur l'apprentissage non supervisé en haute dimension.” 2017. Web. 22 Apr 2021.

Vancouver:

Sebbar M. On unsupervised learning in high dimension : Sur l'apprentissage non supervisé en haute dimension. [Internet] [Doctoral dissertation]. Université Paris-Saclay (ComUE); 2017. [cited 2021 Apr 22]. Available from: http://www.theses.fr/2017SACLG003.

Council of Science Editors:

Sebbar M. On unsupervised learning in high dimension : Sur l'apprentissage non supervisé en haute dimension. [Doctoral Dissertation]. Université Paris-Saclay (ComUE); 2017. Available from: http://www.theses.fr/2017SACLG003

4. Yu, Jia. Distributed parameter and state estimation for wireless sensor networks.

Degree: PhD, 2017, University of Edinburgh

 The research in distributed algorithms is linked with the developments of statistical inference in wireless sensor networks (WSNs) applications. Typically, distributed approaches process the collected… (more)

Subjects/Keywords: distributed algorithms; statistical inference; wireless sensor networks; WSNs applications; EM algorithms; Gaussian mixtures; EM gradient algorithm; Bernoulli model; BFGS formula

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APA (6th Edition):

Yu, J. (2017). Distributed parameter and state estimation for wireless sensor networks. (Doctoral Dissertation). University of Edinburgh. Retrieved from http://hdl.handle.net/1842/28929

Chicago Manual of Style (16th Edition):

Yu, Jia. “Distributed parameter and state estimation for wireless sensor networks.” 2017. Doctoral Dissertation, University of Edinburgh. Accessed April 22, 2021. http://hdl.handle.net/1842/28929.

MLA Handbook (7th Edition):

Yu, Jia. “Distributed parameter and state estimation for wireless sensor networks.” 2017. Web. 22 Apr 2021.

Vancouver:

Yu J. Distributed parameter and state estimation for wireless sensor networks. [Internet] [Doctoral dissertation]. University of Edinburgh; 2017. [cited 2021 Apr 22]. Available from: http://hdl.handle.net/1842/28929.

Council of Science Editors:

Yu J. Distributed parameter and state estimation for wireless sensor networks. [Doctoral Dissertation]. University of Edinburgh; 2017. Available from: http://hdl.handle.net/1842/28929

5. Anderson, Joseph T. Geometric Methods for Robust Data Analysis in High Dimension.

Degree: PhD, Computer Science and Engineering, 2017, The Ohio State University

 Data-driven applications are growing. Machine learning and data analysis now finds both scientific and industrial application in biology, chemistry, geology, medicine, and physics. These applications… (more)

Subjects/Keywords: Computer Science; Applied Mathematics; Machine Learning, Convex Geometry, Data Analysis, Independent Component Analysis, Gaussian Mixtures, Signal Separation

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APA (6th Edition):

Anderson, J. T. (2017). Geometric Methods for Robust Data Analysis in High Dimension. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1488372786126891

Chicago Manual of Style (16th Edition):

Anderson, Joseph T. “Geometric Methods for Robust Data Analysis in High Dimension.” 2017. Doctoral Dissertation, The Ohio State University. Accessed April 22, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1488372786126891.

MLA Handbook (7th Edition):

Anderson, Joseph T. “Geometric Methods for Robust Data Analysis in High Dimension.” 2017. Web. 22 Apr 2021.

Vancouver:

Anderson JT. Geometric Methods for Robust Data Analysis in High Dimension. [Internet] [Doctoral dissertation]. The Ohio State University; 2017. [cited 2021 Apr 22]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1488372786126891.

Council of Science Editors:

Anderson JT. Geometric Methods for Robust Data Analysis in High Dimension. [Doctoral Dissertation]. The Ohio State University; 2017. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1488372786126891

6. Khlaifi, Hajer. Preliminary study for detection and classification of swallowing sound : Étude préliminaire de détection et classification des sons de la déglutition.

Degree: Docteur es, Bioingénierie et Sciences et Technologies de l’Information et des Systèmes : Unité de Recherche Biomécanique et Bio-ingénierie (UMR-7338), 2019, Compiègne

Les maladies altérant le processus de la déglutition sont multiples, affectant la qualité de vie du patient et sa capacité de fonctionner en société. La… (more)

Subjects/Keywords: Décomposition en ondelettes; Sons déglutitoires; GMM; HMM; Wavelet decomposition; Signal processing; Detection; Classification; Swallowing; Deglutition disorders; Sound; Gaussian mixtures models (GMM); Hidden Markov models (HMM); Biosensors

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APA (6th Edition):

Khlaifi, H. (2019). Preliminary study for detection and classification of swallowing sound : Étude préliminaire de détection et classification des sons de la déglutition. (Doctoral Dissertation). Compiègne. Retrieved from http://www.theses.fr/2019COMP2485

Chicago Manual of Style (16th Edition):

Khlaifi, Hajer. “Preliminary study for detection and classification of swallowing sound : Étude préliminaire de détection et classification des sons de la déglutition.” 2019. Doctoral Dissertation, Compiègne. Accessed April 22, 2021. http://www.theses.fr/2019COMP2485.

MLA Handbook (7th Edition):

Khlaifi, Hajer. “Preliminary study for detection and classification of swallowing sound : Étude préliminaire de détection et classification des sons de la déglutition.” 2019. Web. 22 Apr 2021.

Vancouver:

Khlaifi H. Preliminary study for detection and classification of swallowing sound : Étude préliminaire de détection et classification des sons de la déglutition. [Internet] [Doctoral dissertation]. Compiègne; 2019. [cited 2021 Apr 22]. Available from: http://www.theses.fr/2019COMP2485.

Council of Science Editors:

Khlaifi H. Preliminary study for detection and classification of swallowing sound : Étude préliminaire de détection et classification des sons de la déglutition. [Doctoral Dissertation]. Compiègne; 2019. Available from: http://www.theses.fr/2019COMP2485

7. MENSAH DAVID KWAMENA. VARIATIONAL BAYES METHODS IN GAUSSIAN PROCESS REGRESSION.

Degree: 2015, National University of Singapore

Subjects/Keywords: Variational Bayes; Gaussian processes; shape restricted regression; longitudinal data; functional data; functional mixtures

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APA (6th Edition):

KWAMENA, M. D. (2015). VARIATIONAL BAYES METHODS IN GAUSSIAN PROCESS REGRESSION. (Thesis). National University of Singapore. Retrieved from http://scholarbank.nus.edu.sg/handle/10635/124177

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):

KWAMENA, MENSAH DAVID. “VARIATIONAL BAYES METHODS IN GAUSSIAN PROCESS REGRESSION.” 2015. Thesis, National University of Singapore. Accessed April 22, 2021. http://scholarbank.nus.edu.sg/handle/10635/124177.

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

MLA Handbook (7th Edition):

KWAMENA, MENSAH DAVID. “VARIATIONAL BAYES METHODS IN GAUSSIAN PROCESS REGRESSION.” 2015. Web. 22 Apr 2021.

Vancouver:

KWAMENA MD. VARIATIONAL BAYES METHODS IN GAUSSIAN PROCESS REGRESSION. [Internet] [Thesis]. National University of Singapore; 2015. [cited 2021 Apr 22]. Available from: http://scholarbank.nus.edu.sg/handle/10635/124177.

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

Council of Science Editors:

KWAMENA MD. VARIATIONAL BAYES METHODS IN GAUSSIAN PROCESS REGRESSION. [Thesis]. National University of Singapore; 2015. Available from: http://scholarbank.nus.edu.sg/handle/10635/124177

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


University of Southern California

8. Han, Kyu Jeong. Robust speaker clustering under variation in data characteristics.

Degree: PhD, Electrical Engineering, 2009, University of Southern California

 Speaker clustering refers to a process of classifying a set of input speech data (or speech segments) by a speaker identity in an unsupervised way,… (more)

Subjects/Keywords: incremental gaussian mixtures; information change rate; speaker clustering speaker Diarization; speaker modeling

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APA (6th Edition):

Han, K. J. (2009). Robust speaker clustering under variation in data characteristics. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/279173/rec/5624

Chicago Manual of Style (16th Edition):

Han, Kyu Jeong. “Robust speaker clustering under variation in data characteristics.” 2009. Doctoral Dissertation, University of Southern California. Accessed April 22, 2021. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/279173/rec/5624.

MLA Handbook (7th Edition):

Han, Kyu Jeong. “Robust speaker clustering under variation in data characteristics.” 2009. Web. 22 Apr 2021.

Vancouver:

Han KJ. Robust speaker clustering under variation in data characteristics. [Internet] [Doctoral dissertation]. University of Southern California; 2009. [cited 2021 Apr 22]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/279173/rec/5624.

Council of Science Editors:

Han KJ. Robust speaker clustering under variation in data characteristics. [Doctoral Dissertation]. University of Southern California; 2009. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/279173/rec/5624

9. Houdard, Antoine. Some advances in patch-based image denoising : Quelques avancées dans le débruitage d'images par patchs.

Degree: Docteur es, Traitement du signal et des images, 2018, Université Paris-Saclay (ComUE)

Cette thèse s'inscrit dans le contexte des méthodes non locales pour le traitement d'images et a pour application principale le débruitage, bien que les méthodes… (more)

Subjects/Keywords: Débruitage d'image; Traitement d'image par patch; Modèles gaussiens; Modèles de mélanges de gaussiennes; Débruitage global; Agrégation de patchs; Image denoising; Patch-based image processing; Gaussian models; Gaussian mixtures models; Global denoising; Patch aggregation

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APA (6th Edition):

Houdard, A. (2018). Some advances in patch-based image denoising : Quelques avancées dans le débruitage d'images par patchs. (Doctoral Dissertation). Université Paris-Saclay (ComUE). Retrieved from http://www.theses.fr/2018SACLT005

Chicago Manual of Style (16th Edition):

Houdard, Antoine. “Some advances in patch-based image denoising : Quelques avancées dans le débruitage d'images par patchs.” 2018. Doctoral Dissertation, Université Paris-Saclay (ComUE). Accessed April 22, 2021. http://www.theses.fr/2018SACLT005.

MLA Handbook (7th Edition):

Houdard, Antoine. “Some advances in patch-based image denoising : Quelques avancées dans le débruitage d'images par patchs.” 2018. Web. 22 Apr 2021.

Vancouver:

Houdard A. Some advances in patch-based image denoising : Quelques avancées dans le débruitage d'images par patchs. [Internet] [Doctoral dissertation]. Université Paris-Saclay (ComUE); 2018. [cited 2021 Apr 22]. Available from: http://www.theses.fr/2018SACLT005.

Council of Science Editors:

Houdard A. Some advances in patch-based image denoising : Quelques avancées dans le débruitage d'images par patchs. [Doctoral Dissertation]. Université Paris-Saclay (ComUE); 2018. Available from: http://www.theses.fr/2018SACLT005

10. Brkljač Branko. Препознавање облика са ретком репрезентацијом коваријансних матрица и коваријансним дескрипторима.

Degree: 2017, University of Novi Sad

У раду је предложен нови модел за ретку апроксимацију Гаусових компоненти у моделима за статистичко препознавање облика заснованим на Гаусовим смешама, а са циљем… (more)

Subjects/Keywords: Препознавање облика, коваријансна матрица, Гаусове смеше, реткарепрезентација сигнала, дигитална обрада слике, анализа података; Prepoznavanje oblika, kovarijansna matrica, Gausove smeše, retkareprezentacija signala, digitalna obrada slike, analiza podataka; Pattern recognition, covariance matrix, Gaussian mixtures, sparserepresentation of signals, digital image processing, data analysis

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APA (6th Edition):

Branko, B. (2017). Препознавање облика са ретком репрезентацијом коваријансних матрица и коваријансним дескрипторима. (Thesis). University of Novi Sad. Retrieved from https://www.cris.uns.ac.rs/DownloadFileServlet/Disertacija150347865097632.pdf?controlNumber=(BISIS)104951&fileName=150347865097632.pdf&id=10416&source=OATD&language=en ; https://www.cris.uns.ac.rs/record.jsf?recordId=104951&source=OATD&language=en

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):

Branko, Brkljač. “Препознавање облика са ретком репрезентацијом коваријансних матрица и коваријансним дескрипторима.” 2017. Thesis, University of Novi Sad. Accessed April 22, 2021. https://www.cris.uns.ac.rs/DownloadFileServlet/Disertacija150347865097632.pdf?controlNumber=(BISIS)104951&fileName=150347865097632.pdf&id=10416&source=OATD&language=en ; https://www.cris.uns.ac.rs/record.jsf?recordId=104951&source=OATD&language=en.

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

MLA Handbook (7th Edition):

Branko, Brkljač. “Препознавање облика са ретком репрезентацијом коваријансних матрица и коваријансним дескрипторима.” 2017. Web. 22 Apr 2021.

Vancouver:

Branko B. Препознавање облика са ретком репрезентацијом коваријансних матрица и коваријансним дескрипторима. [Internet] [Thesis]. University of Novi Sad; 2017. [cited 2021 Apr 22]. Available from: https://www.cris.uns.ac.rs/DownloadFileServlet/Disertacija150347865097632.pdf?controlNumber=(BISIS)104951&fileName=150347865097632.pdf&id=10416&source=OATD&language=en ; https://www.cris.uns.ac.rs/record.jsf?recordId=104951&source=OATD&language=en.

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

Council of Science Editors:

Branko B. Препознавање облика са ретком репрезентацијом коваријансних матрица и коваријансним дескрипторима. [Thesis]. University of Novi Sad; 2017. Available from: https://www.cris.uns.ac.rs/DownloadFileServlet/Disertacija150347865097632.pdf?controlNumber=(BISIS)104951&fileName=150347865097632.pdf&id=10416&source=OATD&language=en ; https://www.cris.uns.ac.rs/record.jsf?recordId=104951&source=OATD&language=en

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

11. Spinnato, Juliette. Modèles de covariance pour l'analyse et la classification de signaux électroencéphalogrammes : Covariance models for electroencephalogramm signals analysis and classification.

Degree: Docteur es, Mathématiques, 2015, Aix Marseille Université

Cette thèse s’inscrit dans le contexte de l’analyse et de la classification de signaux électroencéphalogrammes (EEG) par des méthodes d’analyse discriminante. Ces signaux multi-capteurs qui… (more)

Subjects/Keywords: Analyse discriminante; Données matricielles; Matrice de covariance séparable; Modèle de mélange gaussien; Modèle linéaire mixte; Décomposition en valeurs singulières; Transformation en ondelettes discrète; Signaux électroencéphalogrammes; Discriminant analysis; Matrix-Based data; Separable covariance matrix; Gaussian mixtures; Linear mixed model; Singular value decomposition; Discrete wavelet transform; Electroencephalogramm signals

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APA (6th Edition):

Spinnato, J. (2015). Modèles de covariance pour l'analyse et la classification de signaux électroencéphalogrammes : Covariance models for electroencephalogramm signals analysis and classification. (Doctoral Dissertation). Aix Marseille Université. Retrieved from http://www.theses.fr/2015AIXM4727

Chicago Manual of Style (16th Edition):

Spinnato, Juliette. “Modèles de covariance pour l'analyse et la classification de signaux électroencéphalogrammes : Covariance models for electroencephalogramm signals analysis and classification.” 2015. Doctoral Dissertation, Aix Marseille Université. Accessed April 22, 2021. http://www.theses.fr/2015AIXM4727.

MLA Handbook (7th Edition):

Spinnato, Juliette. “Modèles de covariance pour l'analyse et la classification de signaux électroencéphalogrammes : Covariance models for electroencephalogramm signals analysis and classification.” 2015. Web. 22 Apr 2021.

Vancouver:

Spinnato J. Modèles de covariance pour l'analyse et la classification de signaux électroencéphalogrammes : Covariance models for electroencephalogramm signals analysis and classification. [Internet] [Doctoral dissertation]. Aix Marseille Université 2015. [cited 2021 Apr 22]. Available from: http://www.theses.fr/2015AIXM4727.

Council of Science Editors:

Spinnato J. Modèles de covariance pour l'analyse et la classification de signaux électroencéphalogrammes : Covariance models for electroencephalogramm signals analysis and classification. [Doctoral Dissertation]. Aix Marseille Université 2015. Available from: http://www.theses.fr/2015AIXM4727


Linköping University

12. Westberg, Daniel. A sensor fusion method for detection of surface laid land mines.

Degree: Electrical Engineering, 2007, Linköping University

Landminor är ett stort problem både under och efter krigstid. De metoder som används för att detektera minor har inte ändrats mycket sedan 1940-talet.… (more)

Subjects/Keywords: mine detection; Gaussian mixtures; expectation-maximization; minimum message length criterion; scatter separabilty criterion; infrared; laser radar; Automatic control; Reglerteknik

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APA (6th Edition):

Westberg, D. (2007). A sensor fusion method for detection of surface laid land mines. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-10479

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):

Westberg, Daniel. “A sensor fusion method for detection of surface laid land mines.” 2007. Thesis, Linköping University. Accessed April 22, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-10479.

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

MLA Handbook (7th Edition):

Westberg, Daniel. “A sensor fusion method for detection of surface laid land mines.” 2007. Web. 22 Apr 2021.

Vancouver:

Westberg D. A sensor fusion method for detection of surface laid land mines. [Internet] [Thesis]. Linköping University; 2007. [cited 2021 Apr 22]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-10479.

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

Council of Science Editors:

Westberg D. A sensor fusion method for detection of surface laid land mines. [Thesis]. Linköping University; 2007. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-10479

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

13. Theeranaew, Wanchat. STUDY ON INFORMATION THEORY: CONNECTION TO CONTROL THEORY, APPROACH AND ANALYSIS FOR COMPUTATION.

Degree: PhD, EECS - System and Control Engineering, 2015, Case Western Reserve University School of Graduate Studies

 This thesis consists of various studies in information theory, including its connection with control theory and the computational aspects of information measures. The first part… (more)

Subjects/Keywords: Engineering; Mathematics; connection, Control Theory, Information theory, entropy, mutual information, computation, gaussian mixtures, hidden Markov model

…of the upper and lower bounds of entropy for Gaussian mixtures, which is one of the key… …improvement of the computation of entropy and mutual information for Gaussian mixtures is also… …lower bounds of entropy for Gaussian mixtures and our approach to improve these bounds are… …Markov Model (HMM) is proposed. For continuous-valued data, a HMM with Gaussian… …is selected. Because any probability distribution can be approximated by a Gaussian mixture… 

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

APA (6th Edition):

Theeranaew, W. (2015). STUDY ON INFORMATION THEORY: CONNECTION TO CONTROL THEORY, APPROACH AND ANALYSIS FOR COMPUTATION. (Doctoral Dissertation). Case Western Reserve University School of Graduate Studies. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case1416847576

Chicago Manual of Style (16th Edition):

Theeranaew, Wanchat. “STUDY ON INFORMATION THEORY: CONNECTION TO CONTROL THEORY, APPROACH AND ANALYSIS FOR COMPUTATION.” 2015. Doctoral Dissertation, Case Western Reserve University School of Graduate Studies. Accessed April 22, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=case1416847576.

MLA Handbook (7th Edition):

Theeranaew, Wanchat. “STUDY ON INFORMATION THEORY: CONNECTION TO CONTROL THEORY, APPROACH AND ANALYSIS FOR COMPUTATION.” 2015. Web. 22 Apr 2021.

Vancouver:

Theeranaew W. STUDY ON INFORMATION THEORY: CONNECTION TO CONTROL THEORY, APPROACH AND ANALYSIS FOR COMPUTATION. [Internet] [Doctoral dissertation]. Case Western Reserve University School of Graduate Studies; 2015. [cited 2021 Apr 22]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1416847576.

Council of Science Editors:

Theeranaew W. STUDY ON INFORMATION THEORY: CONNECTION TO CONTROL THEORY, APPROACH AND ANALYSIS FOR COMPUTATION. [Doctoral Dissertation]. Case Western Reserve University School of Graduate Studies; 2015. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1416847576

14. Ehsandoust, Bahram. Séparation de Sources Dans des Mélanges non-Lineaires : Blind Source Separation in Nonlinear Mixtures.

Degree: Docteur es, Signal image parole telecoms, 2018, Université Grenoble Alpes (ComUE); Sharif University of Technology (Tehran)

La séparation aveugle de sources aveugle (BSS) est une technique d’estimation des différents signaux observés au travers de leurs mélanges à l’aide de plusieurs capteurs,… (more)

Subjects/Keywords: Séparation Aveugle de Sources; Analyse en composantes indépendantes; Mélanges non linéaires; Signaux parcimonieux; Apprentissage sur variétés; Processus Gaussiens; Blind Source Separation; Independent Component Analysis; Nonlinear Mixtures; Sparse Signals; Manifold Learning; Gaussian Processes; 004; 620

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

APA (6th Edition):

Ehsandoust, B. (2018). Séparation de Sources Dans des Mélanges non-Lineaires : Blind Source Separation in Nonlinear Mixtures. (Doctoral Dissertation). Université Grenoble Alpes (ComUE); Sharif University of Technology (Tehran). Retrieved from http://www.theses.fr/2018GREAT033

Chicago Manual of Style (16th Edition):

Ehsandoust, Bahram. “Séparation de Sources Dans des Mélanges non-Lineaires : Blind Source Separation in Nonlinear Mixtures.” 2018. Doctoral Dissertation, Université Grenoble Alpes (ComUE); Sharif University of Technology (Tehran). Accessed April 22, 2021. http://www.theses.fr/2018GREAT033.

MLA Handbook (7th Edition):

Ehsandoust, Bahram. “Séparation de Sources Dans des Mélanges non-Lineaires : Blind Source Separation in Nonlinear Mixtures.” 2018. Web. 22 Apr 2021.

Vancouver:

Ehsandoust B. Séparation de Sources Dans des Mélanges non-Lineaires : Blind Source Separation in Nonlinear Mixtures. [Internet] [Doctoral dissertation]. Université Grenoble Alpes (ComUE); Sharif University of Technology (Tehran); 2018. [cited 2021 Apr 22]. Available from: http://www.theses.fr/2018GREAT033.

Council of Science Editors:

Ehsandoust B. Séparation de Sources Dans des Mélanges non-Lineaires : Blind Source Separation in Nonlinear Mixtures. [Doctoral Dissertation]. Université Grenoble Alpes (ComUE); Sharif University of Technology (Tehran); 2018. Available from: http://www.theses.fr/2018GREAT033

15. Pinto, Rafael Coimbra. Online incremental one-shot learning of temporal sequences.

Degree: 2011, Brazil

Este trabalho introduz novos algoritmos de redes neurais para o processamento online de padrões espaço-temporais, estendendo o algoritmo Incremental Gaussian Mixture Network (IGMN). O algoritmo… (more)

Subjects/Keywords: Inteligência artificial; Redes neurais; Neural networks; Spatio-temporal pattern processing; Gaussian mixtures; Reservoir computing; Time-series prediction

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APA (6th Edition):

Pinto, R. C. (2011). Online incremental one-shot learning of temporal sequences. (Masters Thesis). Brazil. Retrieved from http://hdl.handle.net/10183/49063

Chicago Manual of Style (16th Edition):

Pinto, Rafael Coimbra. “Online incremental one-shot learning of temporal sequences.” 2011. Masters Thesis, Brazil. Accessed April 22, 2021. http://hdl.handle.net/10183/49063.

MLA Handbook (7th Edition):

Pinto, Rafael Coimbra. “Online incremental one-shot learning of temporal sequences.” 2011. Web. 22 Apr 2021.

Vancouver:

Pinto RC. Online incremental one-shot learning of temporal sequences. [Internet] [Masters thesis]. Brazil; 2011. [cited 2021 Apr 22]. Available from: http://hdl.handle.net/10183/49063.

Council of Science Editors:

Pinto RC. Online incremental one-shot learning of temporal sequences. [Masters Thesis]. Brazil; 2011. Available from: http://hdl.handle.net/10183/49063

16. D. Pandini. STUDI PER LA MODELLIZZAZIONE DELLA RIFLETTANZA SPETTRALE NEGLI STRATI PITTORICI.

Degree: 2012, Università degli Studi di Milano

 Nowadays a lot of physical techniques are available in order to have information about an historical painting. They are able to know which chemical elements… (more)

Subjects/Keywords: reflectance; pigment; painting; colorimetry; FORS; Kubelka-Munk; scattering coefficient; absorbtion coefficient; azurite; copper green; prussian blue; pigment layer; pigment powder; pigment grinding; spectrophotometer; remote probes; colorimetric values; pigment mixtures; Canaletto; spectrum; glaze; gaussian spectrum fit; sigmoidal spectrum fit; pigment color; pigment tint; optical fiber; colorimeter; Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin)

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APA (6th Edition):

Pandini, D. (2012). STUDI PER LA MODELLIZZAZIONE DELLA RIFLETTANZA SPETTRALE NEGLI STRATI PITTORICI. (Thesis). Università degli Studi di Milano. Retrieved from http://hdl.handle.net/2434/168396

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):

Pandini, D.. “STUDI PER LA MODELLIZZAZIONE DELLA RIFLETTANZA SPETTRALE NEGLI STRATI PITTORICI.” 2012. Thesis, Università degli Studi di Milano. Accessed April 22, 2021. http://hdl.handle.net/2434/168396.

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

MLA Handbook (7th Edition):

Pandini, D.. “STUDI PER LA MODELLIZZAZIONE DELLA RIFLETTANZA SPETTRALE NEGLI STRATI PITTORICI.” 2012. Web. 22 Apr 2021.

Vancouver:

Pandini D. STUDI PER LA MODELLIZZAZIONE DELLA RIFLETTANZA SPETTRALE NEGLI STRATI PITTORICI. [Internet] [Thesis]. Università degli Studi di Milano; 2012. [cited 2021 Apr 22]. Available from: http://hdl.handle.net/2434/168396.

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

Council of Science Editors:

Pandini D. STUDI PER LA MODELLIZZAZIONE DELLA RIFLETTANZA SPETTRALE NEGLI STRATI PITTORICI. [Thesis]. Università degli Studi di Milano; 2012. Available from: http://hdl.handle.net/2434/168396

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

17. Liu, Peng. Adaptive Mixture Estimation and Subsampling PCA.

Degree: PhD, Sciences, 2009, Case Western Reserve University School of Graduate Studies

 Data mining is important in scientific research, knowledge discovery and decision making. A typical challenge in data mining is that a data set may be… (more)

Subjects/Keywords: Statistics; large data; data mining; mixture models; Gaussian mixtures; parameter estimation; adaptive procedure; partial EM; high-dimensional data; large p small n; dimension reduction; feature selection; subsampling

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

APA (6th Edition):

Liu, P. (2009). Adaptive Mixture Estimation and Subsampling PCA. (Doctoral Dissertation). Case Western Reserve University School of Graduate Studies. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=case1220644686

Chicago Manual of Style (16th Edition):

Liu, Peng. “Adaptive Mixture Estimation and Subsampling PCA.” 2009. Doctoral Dissertation, Case Western Reserve University School of Graduate Studies. Accessed April 22, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=case1220644686.

MLA Handbook (7th Edition):

Liu, Peng. “Adaptive Mixture Estimation and Subsampling PCA.” 2009. Web. 22 Apr 2021.

Vancouver:

Liu P. Adaptive Mixture Estimation and Subsampling PCA. [Internet] [Doctoral dissertation]. Case Western Reserve University School of Graduate Studies; 2009. [cited 2021 Apr 22]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1220644686.

Council of Science Editors:

Liu P. Adaptive Mixture Estimation and Subsampling PCA. [Doctoral Dissertation]. Case Western Reserve University School of Graduate Studies; 2009. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=case1220644686


Erasmus University Rotterdam

18. Ruseckaite, Aiste. New Flexible Models and Design Construction Algorithms for Mixtures and Binary Dependent Variables.

Degree: Department of Econometrics, 2017, Erasmus University Rotterdam

 markdownabstractThis thesis discusses new mixture(-amount) models, choice models and the optimal design of experiments. Two chapters of the thesis relate to the so-called mixture, which… (more)

Subjects/Keywords: Choice experiment; Mixture coordinate-exchange algorithm; Particle swarm optimization; Mixture experiment; Ingredient proportions; Gaussian process prior; Nonparametric Bayes; Mixtures of ingredients; Latent environmental consciousness; Eleectric vehicle; Hybrid; Integrated choice and latent variable model (ICLV)

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APA (6th Edition):

Ruseckaite, A. (2017). New Flexible Models and Design Construction Algorithms for Mixtures and Binary Dependent Variables. (Doctoral Dissertation). Erasmus University Rotterdam. Retrieved from http://hdl.handle.net/1765/94978

Chicago Manual of Style (16th Edition):

Ruseckaite, Aiste. “New Flexible Models and Design Construction Algorithms for Mixtures and Binary Dependent Variables.” 2017. Doctoral Dissertation, Erasmus University Rotterdam. Accessed April 22, 2021. http://hdl.handle.net/1765/94978.

MLA Handbook (7th Edition):

Ruseckaite, Aiste. “New Flexible Models and Design Construction Algorithms for Mixtures and Binary Dependent Variables.” 2017. Web. 22 Apr 2021.

Vancouver:

Ruseckaite A. New Flexible Models and Design Construction Algorithms for Mixtures and Binary Dependent Variables. [Internet] [Doctoral dissertation]. Erasmus University Rotterdam; 2017. [cited 2021 Apr 22]. Available from: http://hdl.handle.net/1765/94978.

Council of Science Editors:

Ruseckaite A. New Flexible Models and Design Construction Algorithms for Mixtures and Binary Dependent Variables. [Doctoral Dissertation]. Erasmus University Rotterdam; 2017. Available from: http://hdl.handle.net/1765/94978

.