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You searched for subject:( Neural networks). Showing records 1 – 30 of 3358 total matches.

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University of Johannesburg

1. De Wet, Anton Petrus Christiaan. An incremental learning system for artificial neural networks .

Degree: 2014, University of Johannesburg

 This dissertation describes the development of a system of Artificial Neural Networks that enables the incremental training of feed forward neural networks using supervised training… (more)

Subjects/Keywords: Neural networks (Computer science); Artificial Neural Networks

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APA (6th Edition):

De Wet, A. P. C. (2014). An incremental learning system for artificial neural networks . (Thesis). University of Johannesburg. Retrieved from http://hdl.handle.net/10210/12024

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):

De Wet, Anton Petrus Christiaan. “An incremental learning system for artificial neural networks .” 2014. Thesis, University of Johannesburg. Accessed November 19, 2017. http://hdl.handle.net/10210/12024.

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

MLA Handbook (7th Edition):

De Wet, Anton Petrus Christiaan. “An incremental learning system for artificial neural networks .” 2014. Web. 19 Nov 2017.

Vancouver:

De Wet APC. An incremental learning system for artificial neural networks . [Internet] [Thesis]. University of Johannesburg; 2014. [cited 2017 Nov 19]. Available from: http://hdl.handle.net/10210/12024.

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

Council of Science Editors:

De Wet APC. An incremental learning system for artificial neural networks . [Thesis]. University of Johannesburg; 2014. Available from: http://hdl.handle.net/10210/12024

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


University of Waterloo

2. Bekolay, Trevor. Learning in large-scale spiking neural networks.

Degree: 2011, University of Waterloo

 Learning is central to the exploration of intelligence. Psychology and machine learning provide high-level explanations of how rational agents learn. Neuroscience provides low-level descriptions of… (more)

Subjects/Keywords: neuroplasticity; learning; neural networks; spiking neural networks

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APA (6th Edition):

Bekolay, T. (2011). Learning in large-scale spiking neural networks. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/6195

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):

Bekolay, Trevor. “Learning in large-scale spiking neural networks.” 2011. Thesis, University of Waterloo. Accessed November 19, 2017. http://hdl.handle.net/10012/6195.

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

MLA Handbook (7th Edition):

Bekolay, Trevor. “Learning in large-scale spiking neural networks.” 2011. Web. 19 Nov 2017.

Vancouver:

Bekolay T. Learning in large-scale spiking neural networks. [Internet] [Thesis]. University of Waterloo; 2011. [cited 2017 Nov 19]. Available from: http://hdl.handle.net/10012/6195.

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

Council of Science Editors:

Bekolay T. Learning in large-scale spiking neural networks. [Thesis]. University of Waterloo; 2011. Available from: http://hdl.handle.net/10012/6195

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


University of Georgia

3. Crowell, Kevin Lee. Precipitation prediction using artificial neural networks.

Degree: MS, Artificial Intelligence, 2008, University of Georgia

 Precipitation, in meteorology, is defined as any product, liquid or solid, of atmospheric water vapor that is accumulated onto the earth’s surface. Water, and thus… (more)

Subjects/Keywords: Artificial Neural Networks

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APA (6th Edition):

Crowell, K. L. (2008). Precipitation prediction using artificial neural networks. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/crowell_kevin_l_200812_ms

Chicago Manual of Style (16th Edition):

Crowell, Kevin Lee. “Precipitation prediction using artificial neural networks.” 2008. Masters Thesis, University of Georgia. Accessed November 19, 2017. http://purl.galileo.usg.edu/uga_etd/crowell_kevin_l_200812_ms.

MLA Handbook (7th Edition):

Crowell, Kevin Lee. “Precipitation prediction using artificial neural networks.” 2008. Web. 19 Nov 2017.

Vancouver:

Crowell KL. Precipitation prediction using artificial neural networks. [Internet] [Masters thesis]. University of Georgia; 2008. [cited 2017 Nov 19]. Available from: http://purl.galileo.usg.edu/uga_etd/crowell_kevin_l_200812_ms.

Council of Science Editors:

Crowell KL. Precipitation prediction using artificial neural networks. [Masters Thesis]. University of Georgia; 2008. Available from: http://purl.galileo.usg.edu/uga_etd/crowell_kevin_l_200812_ms


University of Georgia

4. Martin, Charles Maxwell. Crop yield prediction using artificial neural networks and genetic algorithms.

Degree: MS, Artificial Intelligence, 2009, University of Georgia

 Previous research has established that large-scale climatological phenomena influence local weather conditions in various parts of the world. These weather conditions have a direct effect… (more)

Subjects/Keywords: Artificial Neural Networks

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APA (6th Edition):

Martin, C. M. (2009). Crop yield prediction using artificial neural networks and genetic algorithms. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/martin_charles_m_200912_ms

Chicago Manual of Style (16th Edition):

Martin, Charles Maxwell. “Crop yield prediction using artificial neural networks and genetic algorithms.” 2009. Masters Thesis, University of Georgia. Accessed November 19, 2017. http://purl.galileo.usg.edu/uga_etd/martin_charles_m_200912_ms.

MLA Handbook (7th Edition):

Martin, Charles Maxwell. “Crop yield prediction using artificial neural networks and genetic algorithms.” 2009. Web. 19 Nov 2017.

Vancouver:

Martin CM. Crop yield prediction using artificial neural networks and genetic algorithms. [Internet] [Masters thesis]. University of Georgia; 2009. [cited 2017 Nov 19]. Available from: http://purl.galileo.usg.edu/uga_etd/martin_charles_m_200912_ms.

Council of Science Editors:

Martin CM. Crop yield prediction using artificial neural networks and genetic algorithms. [Masters Thesis]. University of Georgia; 2009. Available from: http://purl.galileo.usg.edu/uga_etd/martin_charles_m_200912_ms


University of Toronto

5. Tieleman, Tijmen. Optimizing Neural Networks that Generate Iimages.

Degree: PhD, 2014, University of Toronto

 Image recognition, also known as computer vision, is one of the most prominent applications of neural networks. The image recognition methods presented in this thesis… (more)

Subjects/Keywords: Neural networks; 0984

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APA (6th Edition):

Tieleman, T. (2014). Optimizing Neural Networks that Generate Iimages. (Doctoral Dissertation). University of Toronto. Retrieved from http://hdl.handle.net/1807/68420

Chicago Manual of Style (16th Edition):

Tieleman, Tijmen. “Optimizing Neural Networks that Generate Iimages.” 2014. Doctoral Dissertation, University of Toronto. Accessed November 19, 2017. http://hdl.handle.net/1807/68420.

MLA Handbook (7th Edition):

Tieleman, Tijmen. “Optimizing Neural Networks that Generate Iimages.” 2014. Web. 19 Nov 2017.

Vancouver:

Tieleman T. Optimizing Neural Networks that Generate Iimages. [Internet] [Doctoral dissertation]. University of Toronto; 2014. [cited 2017 Nov 19]. Available from: http://hdl.handle.net/1807/68420.

Council of Science Editors:

Tieleman T. Optimizing Neural Networks that Generate Iimages. [Doctoral Dissertation]. University of Toronto; 2014. Available from: http://hdl.handle.net/1807/68420


University of Waterloo

6. Caterini, Anthony. A Novel Mathematical Framework for the Analysis of Neural Networks.

Degree: 2017, University of Waterloo

 Over the past decade, Deep Neural Networks (DNNs) have become very popular models for processing large amounts of data because of their successful application in… (more)

Subjects/Keywords: Neural Networks; Convolutional Neural Networks; Deep Neural Networks; Machine Learning; Recurrent Neural Networks

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APA (6th Edition):

Caterini, A. (2017). A Novel Mathematical Framework for the Analysis of Neural Networks. (Thesis). University of Waterloo. Retrieved from http://hdl.handle.net/10012/12173

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):

Caterini, Anthony. “A Novel Mathematical Framework for the Analysis of Neural Networks.” 2017. Thesis, University of Waterloo. Accessed November 19, 2017. http://hdl.handle.net/10012/12173.

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

MLA Handbook (7th Edition):

Caterini, Anthony. “A Novel Mathematical Framework for the Analysis of Neural Networks.” 2017. Web. 19 Nov 2017.

Vancouver:

Caterini A. A Novel Mathematical Framework for the Analysis of Neural Networks. [Internet] [Thesis]. University of Waterloo; 2017. [cited 2017 Nov 19]. Available from: http://hdl.handle.net/10012/12173.

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

Council of Science Editors:

Caterini A. A Novel Mathematical Framework for the Analysis of Neural Networks. [Thesis]. University of Waterloo; 2017. Available from: http://hdl.handle.net/10012/12173

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


Ryerson University

7. Yong Xia. Experimental implementation of an artificial neural network-based active vibration control.

Degree: MASc, Mechanical Engineering, 2010, Ryerson University

 Vibration control strategies strive to reduce the effect of harmful vibrations on machinery and people. In general, these strategies are classified as passive or active.… (more)

Subjects/Keywords: Vibration; Neural networks

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APA (6th Edition):

Xia, Y. (2010). Experimental implementation of an artificial neural network-based active vibration control. (Masters Thesis). Ryerson University. Retrieved from http://digital.library.ryerson.ca/islandora/object/RULA%3A535 ;

Chicago Manual of Style (16th Edition):

Xia, Yong. “Experimental implementation of an artificial neural network-based active vibration control.” 2010. Masters Thesis, Ryerson University. Accessed November 19, 2017. http://digital.library.ryerson.ca/islandora/object/RULA%3A535 ;.

MLA Handbook (7th Edition):

Xia, Yong. “Experimental implementation of an artificial neural network-based active vibration control.” 2010. Web. 19 Nov 2017.

Vancouver:

Xia Y. Experimental implementation of an artificial neural network-based active vibration control. [Internet] [Masters thesis]. Ryerson University; 2010. [cited 2017 Nov 19]. Available from: http://digital.library.ryerson.ca/islandora/object/RULA%3A535 ;.

Council of Science Editors:

Xia Y. Experimental implementation of an artificial neural network-based active vibration control. [Masters Thesis]. Ryerson University; 2010. Available from: http://digital.library.ryerson.ca/islandora/object/RULA%3A535 ;


ETH Zürich

8. Neil, Daniel. Deep Neural Networks and Hardware Systems for Event-driven Data.

Degree: 2017, ETH Zürich

 Event-based sensors, built with biological inspiration, differ greatly from traditional sensor types. A standard vision sensor uses a pixel array to produce a frame containing… (more)

Subjects/Keywords: Deep Neural Networks; Event-driven sensors; Deep neural networks (DNNs); Spiking deep neural networks; Recurrent Neural Networks; Convolutional neural networks

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APA (6th Edition):

Neil, D. (2017). Deep Neural Networks and Hardware Systems for Event-driven Data. (Doctoral Dissertation). ETH Zürich. Retrieved from http://hdl.handle.net/20.500.11850/168865

Chicago Manual of Style (16th Edition):

Neil, Daniel. “Deep Neural Networks and Hardware Systems for Event-driven Data.” 2017. Doctoral Dissertation, ETH Zürich. Accessed November 19, 2017. http://hdl.handle.net/20.500.11850/168865.

MLA Handbook (7th Edition):

Neil, Daniel. “Deep Neural Networks and Hardware Systems for Event-driven Data.” 2017. Web. 19 Nov 2017.

Vancouver:

Neil D. Deep Neural Networks and Hardware Systems for Event-driven Data. [Internet] [Doctoral dissertation]. ETH Zürich; 2017. [cited 2017 Nov 19]. Available from: http://hdl.handle.net/20.500.11850/168865.

Council of Science Editors:

Neil D. Deep Neural Networks and Hardware Systems for Event-driven Data. [Doctoral Dissertation]. ETH Zürich; 2017. Available from: http://hdl.handle.net/20.500.11850/168865


Rutgers University

9. Zhao, Shunbing. Neuromodulation of inhibitory feedback to pacemaker neurons and its consequent role in stabilizing the output of the neuronal network:.

Degree: PhD, Biology, 2009, Rutgers University

Stable oscillations can be important for the proper function of neuronal networks. Rhythmic movements, for example, often rely on stable input from central pattern generator… (more)

Subjects/Keywords: Neural networks (Neurobiology); Neural transmission; Electrophysiology

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APA (6th Edition):

Zhao, S. (2009). Neuromodulation of inhibitory feedback to pacemaker neurons and its consequent role in stabilizing the output of the neuronal network:. (Doctoral Dissertation). Rutgers University. Retrieved from http://hdl.rutgers.edu/1782.2/rucore10002600001.ETD.000051647

Chicago Manual of Style (16th Edition):

Zhao, Shunbing. “Neuromodulation of inhibitory feedback to pacemaker neurons and its consequent role in stabilizing the output of the neuronal network:.” 2009. Doctoral Dissertation, Rutgers University. Accessed November 19, 2017. http://hdl.rutgers.edu/1782.2/rucore10002600001.ETD.000051647.

MLA Handbook (7th Edition):

Zhao, Shunbing. “Neuromodulation of inhibitory feedback to pacemaker neurons and its consequent role in stabilizing the output of the neuronal network:.” 2009. Web. 19 Nov 2017.

Vancouver:

Zhao S. Neuromodulation of inhibitory feedback to pacemaker neurons and its consequent role in stabilizing the output of the neuronal network:. [Internet] [Doctoral dissertation]. Rutgers University; 2009. [cited 2017 Nov 19]. Available from: http://hdl.rutgers.edu/1782.2/rucore10002600001.ETD.000051647.

Council of Science Editors:

Zhao S. Neuromodulation of inhibitory feedback to pacemaker neurons and its consequent role in stabilizing the output of the neuronal network:. [Doctoral Dissertation]. Rutgers University; 2009. Available from: http://hdl.rutgers.edu/1782.2/rucore10002600001.ETD.000051647


Bucknell University

10. Mukhopadhyay, Himadri. THE RESONATE-AND-FIRE NEURON: TIME DEPENDENT AND FREQUENCY SELECTIVE NEURONS IN NEURAL NETWORKS.

Degree: 2010, Bucknell University

 The means through which the nervous system perceives its environment is one of the most fascinating questions in contemporary science. Our endeavors to comprehend the… (more)

Subjects/Keywords: Neural Signals; Neural Networks; Temporal Backpropagation

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APA (6th Edition):

Mukhopadhyay, H. (2010). THE RESONATE-AND-FIRE NEURON: TIME DEPENDENT AND FREQUENCY SELECTIVE NEURONS IN NEURAL NETWORKS. (Thesis). Bucknell University. Retrieved from http://digitalcommons.bucknell.edu/masters_theses/23

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):

Mukhopadhyay, Himadri. “THE RESONATE-AND-FIRE NEURON: TIME DEPENDENT AND FREQUENCY SELECTIVE NEURONS IN NEURAL NETWORKS.” 2010. Thesis, Bucknell University. Accessed November 19, 2017. http://digitalcommons.bucknell.edu/masters_theses/23.

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

MLA Handbook (7th Edition):

Mukhopadhyay, Himadri. “THE RESONATE-AND-FIRE NEURON: TIME DEPENDENT AND FREQUENCY SELECTIVE NEURONS IN NEURAL NETWORKS.” 2010. Web. 19 Nov 2017.

Vancouver:

Mukhopadhyay H. THE RESONATE-AND-FIRE NEURON: TIME DEPENDENT AND FREQUENCY SELECTIVE NEURONS IN NEURAL NETWORKS. [Internet] [Thesis]. Bucknell University; 2010. [cited 2017 Nov 19]. Available from: http://digitalcommons.bucknell.edu/masters_theses/23.

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

Council of Science Editors:

Mukhopadhyay H. THE RESONATE-AND-FIRE NEURON: TIME DEPENDENT AND FREQUENCY SELECTIVE NEURONS IN NEURAL NETWORKS. [Thesis]. Bucknell University; 2010. Available from: http://digitalcommons.bucknell.edu/masters_theses/23

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


University of Michigan

11. Reed, Scott. Deep Neural Networks for Visual Reasoning, Program Induction, and Text-to-Image Synthesis.

Degree: PhD, Computer Science & Engineering, 2016, University of Michigan

 Deep neural networks excel at pattern recognition, especially in the setting of large scale supervised learning. A combination of better hardware, more data, and algorithmic… (more)

Subjects/Keywords: neural networks; Computer Science; Engineering

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APA (6th Edition):

Reed, S. (2016). Deep Neural Networks for Visual Reasoning, Program Induction, and Text-to-Image Synthesis. (Doctoral Dissertation). University of Michigan. Retrieved from http://hdl.handle.net/2027.42/135763

Chicago Manual of Style (16th Edition):

Reed, Scott. “Deep Neural Networks for Visual Reasoning, Program Induction, and Text-to-Image Synthesis.” 2016. Doctoral Dissertation, University of Michigan. Accessed November 19, 2017. http://hdl.handle.net/2027.42/135763.

MLA Handbook (7th Edition):

Reed, Scott. “Deep Neural Networks for Visual Reasoning, Program Induction, and Text-to-Image Synthesis.” 2016. Web. 19 Nov 2017.

Vancouver:

Reed S. Deep Neural Networks for Visual Reasoning, Program Induction, and Text-to-Image Synthesis. [Internet] [Doctoral dissertation]. University of Michigan; 2016. [cited 2017 Nov 19]. Available from: http://hdl.handle.net/2027.42/135763.

Council of Science Editors:

Reed S. Deep Neural Networks for Visual Reasoning, Program Induction, and Text-to-Image Synthesis. [Doctoral Dissertation]. University of Michigan; 2016. Available from: http://hdl.handle.net/2027.42/135763


University of Georgia

12. Ramyaa, Ramyaa. Frost prediction using Artificial Neural Networks: a classification approach.

Degree: MS, Artificial Intelligence, 2004, University of Georgia

 Air temperatures below freezing can damage plants. Irrigation is the most widely practiced frost protection measure. However, growers need information about when to start irrigating,… (more)

Subjects/Keywords: Neural Networks

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APA (6th Edition):

Ramyaa, R. (2004). Frost prediction using Artificial Neural Networks: a classification approach. (Masters Thesis). University of Georgia. Retrieved from http://purl.galileo.usg.edu/uga_etd/ramyaa_ramyaa_200408_ms2

Chicago Manual of Style (16th Edition):

Ramyaa, Ramyaa. “Frost prediction using Artificial Neural Networks: a classification approach.” 2004. Masters Thesis, University of Georgia. Accessed November 19, 2017. http://purl.galileo.usg.edu/uga_etd/ramyaa_ramyaa_200408_ms2.

MLA Handbook (7th Edition):

Ramyaa, Ramyaa. “Frost prediction using Artificial Neural Networks: a classification approach.” 2004. Web. 19 Nov 2017.

Vancouver:

Ramyaa R. Frost prediction using Artificial Neural Networks: a classification approach. [Internet] [Masters thesis]. University of Georgia; 2004. [cited 2017 Nov 19]. Available from: http://purl.galileo.usg.edu/uga_etd/ramyaa_ramyaa_200408_ms2.

Council of Science Editors:

Ramyaa R. Frost prediction using Artificial Neural Networks: a classification approach. [Masters Thesis]. University of Georgia; 2004. Available from: http://purl.galileo.usg.edu/uga_etd/ramyaa_ramyaa_200408_ms2


University of Toronto

13. Tryphonas, Marinos. Modeling Hedge Fund Performance Using Neural Network Models.

Degree: 2012, University of Toronto

Hedge fund performance is modeled from publically available data using feed-forward neural networks trained using a resilient backpropagation algorithm. The neural network’s performance is then… (more)

Subjects/Keywords: Neural Networks; Hedge Funds; 0542

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APA (6th Edition):

Tryphonas, M. (2012). Modeling Hedge Fund Performance Using Neural Network Models. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/32497

Chicago Manual of Style (16th Edition):

Tryphonas, Marinos. “Modeling Hedge Fund Performance Using Neural Network Models.” 2012. Masters Thesis, University of Toronto. Accessed November 19, 2017. http://hdl.handle.net/1807/32497.

MLA Handbook (7th Edition):

Tryphonas, Marinos. “Modeling Hedge Fund Performance Using Neural Network Models.” 2012. Web. 19 Nov 2017.

Vancouver:

Tryphonas M. Modeling Hedge Fund Performance Using Neural Network Models. [Internet] [Masters thesis]. University of Toronto; 2012. [cited 2017 Nov 19]. Available from: http://hdl.handle.net/1807/32497.

Council of Science Editors:

Tryphonas M. Modeling Hedge Fund Performance Using Neural Network Models. [Masters Thesis]. University of Toronto; 2012. Available from: http://hdl.handle.net/1807/32497


University of Toronto

14. Liu, Chen. Probabilistic Siamese Networks for Learning Representations.

Degree: 2013, University of Toronto

We explore the training of deep neural networks to produce vector representations using weakly labelled information in the form of binary similarity labels for pairs… (more)

Subjects/Keywords: Machine Learning; Neural Networks; 0544

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APA (6th Edition):

Liu, C. (2013). Probabilistic Siamese Networks for Learning Representations. (Masters Thesis). University of Toronto. Retrieved from http://hdl.handle.net/1807/43097

Chicago Manual of Style (16th Edition):

Liu, Chen. “Probabilistic Siamese Networks for Learning Representations.” 2013. Masters Thesis, University of Toronto. Accessed November 19, 2017. http://hdl.handle.net/1807/43097.

MLA Handbook (7th Edition):

Liu, Chen. “Probabilistic Siamese Networks for Learning Representations.” 2013. Web. 19 Nov 2017.

Vancouver:

Liu C. Probabilistic Siamese Networks for Learning Representations. [Internet] [Masters thesis]. University of Toronto; 2013. [cited 2017 Nov 19]. Available from: http://hdl.handle.net/1807/43097.

Council of Science Editors:

Liu C. Probabilistic Siamese Networks for Learning Representations. [Masters Thesis]. University of Toronto; 2013. Available from: http://hdl.handle.net/1807/43097


Anna University

15. Ashok V. Certain investigations on noninvasive optical blood glucose concentration prediction system using modified haar wavelet transform and neural networks;.

Degree: noninvasive optical blood glucose concentration prediction system using modified haar wavelet transform and neural networks, 2014, Anna University

Diabetes Mellitus is the most well known Constitutional disorder of newlineCarbohydrates Metabolism characterized by inadequate Secretion or newlineutilization of insulin This disorder condition reduces the… (more)

Subjects/Keywords: neural networks; noninvasive; optical blood

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APA (6th Edition):

V, A. (2014). Certain investigations on noninvasive optical blood glucose concentration prediction system using modified haar wavelet transform and neural networks;. (Thesis). Anna University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/22940

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):

V, Ashok. “Certain investigations on noninvasive optical blood glucose concentration prediction system using modified haar wavelet transform and neural networks;.” 2014. Thesis, Anna University. Accessed November 19, 2017. http://shodhganga.inflibnet.ac.in/handle/10603/22940.

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

MLA Handbook (7th Edition):

V, Ashok. “Certain investigations on noninvasive optical blood glucose concentration prediction system using modified haar wavelet transform and neural networks;.” 2014. Web. 19 Nov 2017.

Vancouver:

V A. Certain investigations on noninvasive optical blood glucose concentration prediction system using modified haar wavelet transform and neural networks;. [Internet] [Thesis]. Anna University; 2014. [cited 2017 Nov 19]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/22940.

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

Council of Science Editors:

V A. Certain investigations on noninvasive optical blood glucose concentration prediction system using modified haar wavelet transform and neural networks;. [Thesis]. Anna University; 2014. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/22940

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

16. Vieira, Lucimar Sasso. Conversão de voz baseada na transformada wavelet.

Degree: Mestrado, Física Aplicada, 2007, University of São Paulo

Dentre as inúmeras técnicas de conversão de voz utilizadas atualmente, aquelas baseadas em bancos de filtros wavelet, associadas com redes neurais artificiais,têm se destacado. Este… (more)

Subjects/Keywords: Neural networks; Voice conversion; Wavelets

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APA (6th Edition):

Vieira, L. S. (2007). Conversão de voz baseada na transformada wavelet. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/76/76132/tde-05092007-192622/ ;

Chicago Manual of Style (16th Edition):

Vieira, Lucimar Sasso. “Conversão de voz baseada na transformada wavelet.” 2007. Masters Thesis, University of São Paulo. Accessed November 19, 2017. http://www.teses.usp.br/teses/disponiveis/76/76132/tde-05092007-192622/ ;.

MLA Handbook (7th Edition):

Vieira, Lucimar Sasso. “Conversão de voz baseada na transformada wavelet.” 2007. Web. 19 Nov 2017.

Vancouver:

Vieira LS. Conversão de voz baseada na transformada wavelet. [Internet] [Masters thesis]. University of São Paulo; 2007. [cited 2017 Nov 19]. Available from: http://www.teses.usp.br/teses/disponiveis/76/76132/tde-05092007-192622/ ;.

Council of Science Editors:

Vieira LS. Conversão de voz baseada na transformada wavelet. [Masters Thesis]. University of São Paulo; 2007. Available from: http://www.teses.usp.br/teses/disponiveis/76/76132/tde-05092007-192622/ ;


Rochester Institute of Technology

17. Golwalla, Arif K. A Hardware approach to neural networks silicon retina.

Degree: Computer Engineering, 1994, Rochester Institute of Technology

 The primary goal of this thesis was to emulate the function of the biological eye in silicon. In both neural and silicon technologies, the active… (more)

Subjects/Keywords: Neural networks

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APA (6th Edition):

Golwalla, A. K. (1994). A Hardware approach to neural networks silicon retina. (Thesis). Rochester Institute of Technology. Retrieved from http://scholarworks.rit.edu/theses/4617

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):

Golwalla, Arif K. “A Hardware approach to neural networks silicon retina.” 1994. Thesis, Rochester Institute of Technology. Accessed November 19, 2017. http://scholarworks.rit.edu/theses/4617.

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

MLA Handbook (7th Edition):

Golwalla, Arif K. “A Hardware approach to neural networks silicon retina.” 1994. Web. 19 Nov 2017.

Vancouver:

Golwalla AK. A Hardware approach to neural networks silicon retina. [Internet] [Thesis]. Rochester Institute of Technology; 1994. [cited 2017 Nov 19]. Available from: http://scholarworks.rit.edu/theses/4617.

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

Council of Science Editors:

Golwalla AK. A Hardware approach to neural networks silicon retina. [Thesis]. Rochester Institute of Technology; 1994. Available from: http://scholarworks.rit.edu/theses/4617

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


University of North Carolina – Greensboro

18. Beaty, Roger E. Brain networks underlying figurative language production.

Degree: 2015, University of North Carolina – Greensboro

 Metaphor is a common form of figurative language, yet little is known about how the brain produces novel figurative expressions. Related research suggests that dynamic… (more)

Subjects/Keywords: Neural networks (Neurobiology); Neurolinguistics; Metaphor

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APA (6th Edition):

Beaty, R. E. (2015). Brain networks underlying figurative language production. (Doctoral Dissertation). University of North Carolina – Greensboro. Retrieved from http://libres.uncg.edu/ir/listing.aspx?styp=ti&id=18400

Chicago Manual of Style (16th Edition):

Beaty, Roger E. “Brain networks underlying figurative language production.” 2015. Doctoral Dissertation, University of North Carolina – Greensboro. Accessed November 19, 2017. http://libres.uncg.edu/ir/listing.aspx?styp=ti&id=18400.

MLA Handbook (7th Edition):

Beaty, Roger E. “Brain networks underlying figurative language production.” 2015. Web. 19 Nov 2017.

Vancouver:

Beaty RE. Brain networks underlying figurative language production. [Internet] [Doctoral dissertation]. University of North Carolina – Greensboro; 2015. [cited 2017 Nov 19]. Available from: http://libres.uncg.edu/ir/listing.aspx?styp=ti&id=18400.

Council of Science Editors:

Beaty RE. Brain networks underlying figurative language production. [Doctoral Dissertation]. University of North Carolina – Greensboro; 2015. Available from: http://libres.uncg.edu/ir/listing.aspx?styp=ti&id=18400

19. Samidurai, R. Studies and stability of non linear impulsive neural networks; -.

Degree: Mathematics, 2010, Periyar University

Abstract available in image PDF

References p.116-130

Advisors/Committee Members: Marshal, Anthoni S.

Subjects/Keywords: Neural Networks

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APA (6th Edition):

Samidurai, R. (2010). Studies and stability of non linear impulsive neural networks; -. (Thesis). Periyar University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/5208

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):

Samidurai, R. “Studies and stability of non linear impulsive neural networks; -.” 2010. Thesis, Periyar University. Accessed November 19, 2017. http://shodhganga.inflibnet.ac.in/handle/10603/5208.

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

MLA Handbook (7th Edition):

Samidurai, R. “Studies and stability of non linear impulsive neural networks; -.” 2010. Web. 19 Nov 2017.

Vancouver:

Samidurai R. Studies and stability of non linear impulsive neural networks; -. [Internet] [Thesis]. Periyar University; 2010. [cited 2017 Nov 19]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/5208.

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

Council of Science Editors:

Samidurai R. Studies and stability of non linear impulsive neural networks; -. [Thesis]. Periyar University; 2010. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/5208

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

20. Sujatha P. Image steganalysis using artificial neural networks.

Degree: Computing Sciences, 2013, Vels University

This research work presents the steganalysis of steganographic images under predefined way of hiding information. Hiding information in the cover image is done by different… (more)

Subjects/Keywords: Computing Sciences; Artificial Neural Networks

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APA (6th Edition):

P, S. (2013). Image steganalysis using artificial neural networks. (Thesis). Vels University. Retrieved from http://shodhganga.inflibnet.ac.in/handle/10603/8912

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):

P, Sujatha. “Image steganalysis using artificial neural networks.” 2013. Thesis, Vels University. Accessed November 19, 2017. http://shodhganga.inflibnet.ac.in/handle/10603/8912.

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

MLA Handbook (7th Edition):

P, Sujatha. “Image steganalysis using artificial neural networks.” 2013. Web. 19 Nov 2017.

Vancouver:

P S. Image steganalysis using artificial neural networks. [Internet] [Thesis]. Vels University; 2013. [cited 2017 Nov 19]. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/8912.

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

Council of Science Editors:

P S. Image steganalysis using artificial neural networks. [Thesis]. Vels University; 2013. Available from: http://shodhganga.inflibnet.ac.in/handle/10603/8912

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


Nelson Mandela Metropolitan University

21. Pretorius, Christiaan Johannes. Artificial neural networks as simulators for behavioural evolution in evolutionary robotics.

Degree: MSc, Faculty of Science, 2010, Nelson Mandela Metropolitan University

 Robotic simulators for use in Evolutionary Robotics (ER) have certain challenges associated with the complexity of their construction and the accuracy of predictions made by… (more)

Subjects/Keywords: Neural networks (Computer science); Robotics

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APA (6th Edition):

Pretorius, C. J. (2010). Artificial neural networks as simulators for behavioural evolution in evolutionary robotics. (Masters Thesis). Nelson Mandela Metropolitan University. Retrieved from http://hdl.handle.net/10948/1476

Chicago Manual of Style (16th Edition):

Pretorius, Christiaan Johannes. “Artificial neural networks as simulators for behavioural evolution in evolutionary robotics.” 2010. Masters Thesis, Nelson Mandela Metropolitan University. Accessed November 19, 2017. http://hdl.handle.net/10948/1476.

MLA Handbook (7th Edition):

Pretorius, Christiaan Johannes. “Artificial neural networks as simulators for behavioural evolution in evolutionary robotics.” 2010. Web. 19 Nov 2017.

Vancouver:

Pretorius CJ. Artificial neural networks as simulators for behavioural evolution in evolutionary robotics. [Internet] [Masters thesis]. Nelson Mandela Metropolitan University; 2010. [cited 2017 Nov 19]. Available from: http://hdl.handle.net/10948/1476.

Council of Science Editors:

Pretorius CJ. Artificial neural networks as simulators for behavioural evolution in evolutionary robotics. [Masters Thesis]. Nelson Mandela Metropolitan University; 2010. Available from: http://hdl.handle.net/10948/1476


University of Aberdeen

22. Goetz, Thomas. From synapse to behaviour : selective modulation of neuronal networks.

Degree: 2008, University of Aberdeen

In this thesis, I describe the development of a novel method to selectively modulate neural activity cell-type selectively. Binding of Zolpidem, an allosteric modulator that enhances GABAa receptor function and the inverse agonist β-carboline, require a phenylalanine residue (F77) in the γ subunit.

Subjects/Keywords: 612.81; Neural networks (Neurobiology); GABA

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APA (6th Edition):

Goetz, T. (2008). From synapse to behaviour : selective modulation of neuronal networks. (Doctoral Dissertation). University of Aberdeen. Retrieved from http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=24802 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.493492

Chicago Manual of Style (16th Edition):

Goetz, Thomas. “From synapse to behaviour : selective modulation of neuronal networks.” 2008. Doctoral Dissertation, University of Aberdeen. Accessed November 19, 2017. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=24802 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.493492.

MLA Handbook (7th Edition):

Goetz, Thomas. “From synapse to behaviour : selective modulation of neuronal networks.” 2008. Web. 19 Nov 2017.

Vancouver:

Goetz T. From synapse to behaviour : selective modulation of neuronal networks. [Internet] [Doctoral dissertation]. University of Aberdeen; 2008. [cited 2017 Nov 19]. Available from: http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=24802 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.493492.

Council of Science Editors:

Goetz T. From synapse to behaviour : selective modulation of neuronal networks. [Doctoral Dissertation]. University of Aberdeen; 2008. Available from: http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=24802 ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.493492


Vilnius University

23. Vasiliauskaitė, Vilma. Spiečiaus intelekto taikymo finansų rinkose analizė ir optimizavimas.

Degree: Master, 2014, Vilnius University

Prekiaujant vertybiniais popieriais, svarbiausia yra priimti teisingą sprendimą: pirkti arba parduoti. Daugelis investuotojų prieš priimdami sprendimą atkreipia dėmesį į pasirinktos akcijos kainos kitimo grafiką ir… (more)

Subjects/Keywords: Swarm Intelligent; Neural networks

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APA (6th Edition):

Vasiliauskaitė, V. (2014). Spiečiaus intelekto taikymo finansų rinkose analizė ir optimizavimas. (Masters Thesis). Vilnius University. Retrieved from http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20140623_183138-57850 ;

Chicago Manual of Style (16th Edition):

Vasiliauskaitė, Vilma. “Spiečiaus intelekto taikymo finansų rinkose analizė ir optimizavimas.” 2014. Masters Thesis, Vilnius University. Accessed November 19, 2017. http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20140623_183138-57850 ;.

MLA Handbook (7th Edition):

Vasiliauskaitė, Vilma. “Spiečiaus intelekto taikymo finansų rinkose analizė ir optimizavimas.” 2014. Web. 19 Nov 2017.

Vancouver:

Vasiliauskaitė V. Spiečiaus intelekto taikymo finansų rinkose analizė ir optimizavimas. [Internet] [Masters thesis]. Vilnius University; 2014. [cited 2017 Nov 19]. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20140623_183138-57850 ;.

Council of Science Editors:

Vasiliauskaitė V. Spiečiaus intelekto taikymo finansų rinkose analizė ir optimizavimas. [Masters Thesis]. Vilnius University; 2014. Available from: http://vddb.laba.lt/obj/LT-eLABa-0001:E.02~2008~D_20140623_183138-57850 ;


Mississippi State University

24. Tiruveedhula, Mohan P. ARTIFICIAL NEURAL NETWORKS TO DETECT FOREST FIRE PRONE AREAS IN THE SOUTHEAST FIRE DISTRICT OF MISSISSIPPI.

Degree: MS, Geosciences, 2008, Mississippi State University

 An analysis of the fire occurrences parameters is essential to save human lives, property, timber resources and conservation of biodiversity. Data conversion formats such as… (more)

Subjects/Keywords: Forest fires; Artificial Neural networks

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APA (6th Edition):

Tiruveedhula, M. P. (2008). ARTIFICIAL NEURAL NETWORKS TO DETECT FOREST FIRE PRONE AREAS IN THE SOUTHEAST FIRE DISTRICT OF MISSISSIPPI. (Masters Thesis). Mississippi State University. Retrieved from http://sun.library.msstate.edu/ETD-db/theses/available/etd-05192008-120103/ ;

Chicago Manual of Style (16th Edition):

Tiruveedhula, Mohan P. “ARTIFICIAL NEURAL NETWORKS TO DETECT FOREST FIRE PRONE AREAS IN THE SOUTHEAST FIRE DISTRICT OF MISSISSIPPI.” 2008. Masters Thesis, Mississippi State University. Accessed November 19, 2017. http://sun.library.msstate.edu/ETD-db/theses/available/etd-05192008-120103/ ;.

MLA Handbook (7th Edition):

Tiruveedhula, Mohan P. “ARTIFICIAL NEURAL NETWORKS TO DETECT FOREST FIRE PRONE AREAS IN THE SOUTHEAST FIRE DISTRICT OF MISSISSIPPI.” 2008. Web. 19 Nov 2017.

Vancouver:

Tiruveedhula MP. ARTIFICIAL NEURAL NETWORKS TO DETECT FOREST FIRE PRONE AREAS IN THE SOUTHEAST FIRE DISTRICT OF MISSISSIPPI. [Internet] [Masters thesis]. Mississippi State University; 2008. [cited 2017 Nov 19]. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-05192008-120103/ ;.

Council of Science Editors:

Tiruveedhula MP. ARTIFICIAL NEURAL NETWORKS TO DETECT FOREST FIRE PRONE AREAS IN THE SOUTHEAST FIRE DISTRICT OF MISSISSIPPI. [Masters Thesis]. Mississippi State University; 2008. Available from: http://sun.library.msstate.edu/ETD-db/theses/available/etd-05192008-120103/ ;


Indiana University of Pennsylvania

25. Gresavage, Thomas. A Neural Networks Approach to Determining Angle and Scale of Partially Occluded Objects.

Degree: MS, Mathematics, 2016, Indiana University of Pennsylvania

  A team of biological researchers wishes to investigate the eating behaviors of local insects to determine whether they prefer indigenous or invasive plant species.… (more)

Subjects/Keywords: computer vision; neural networks; python

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APA (6th Edition):

Gresavage, T. (2016). A Neural Networks Approach to Determining Angle and Scale of Partially Occluded Objects. (Thesis). Indiana University of Pennsylvania. Retrieved from http://knowledge.library.iup.edu/etd/1408

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):

Gresavage, Thomas. “A Neural Networks Approach to Determining Angle and Scale of Partially Occluded Objects.” 2016. Thesis, Indiana University of Pennsylvania. Accessed November 19, 2017. http://knowledge.library.iup.edu/etd/1408.

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

MLA Handbook (7th Edition):

Gresavage, Thomas. “A Neural Networks Approach to Determining Angle and Scale of Partially Occluded Objects.” 2016. Web. 19 Nov 2017.

Vancouver:

Gresavage T. A Neural Networks Approach to Determining Angle and Scale of Partially Occluded Objects. [Internet] [Thesis]. Indiana University of Pennsylvania; 2016. [cited 2017 Nov 19]. Available from: http://knowledge.library.iup.edu/etd/1408.

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

Council of Science Editors:

Gresavage T. A Neural Networks Approach to Determining Angle and Scale of Partially Occluded Objects. [Thesis]. Indiana University of Pennsylvania; 2016. Available from: http://knowledge.library.iup.edu/etd/1408

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


California State University – Sacramento

26. Sirinonrang, Sukanya. On-line measurements using neural networks and soft computing for the control of glass production furnace.

Degree: MS, Mechanical Engineering, 2010, California State University – Sacramento

 Liquefied petroleum (LP) gas is used as a backup energy system for glass production furnace. LP gas is mixed with air at a desired ratio… (more)

Subjects/Keywords: ANFIS; Glass production; Neural networks

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APA (6th Edition):

Sirinonrang, S. (2010). On-line measurements using neural networks and soft computing for the control of glass production furnace. (Masters Thesis). California State University – Sacramento. Retrieved from http://hdl.handle.net/10211.9/834

Chicago Manual of Style (16th Edition):

Sirinonrang, Sukanya. “On-line measurements using neural networks and soft computing for the control of glass production furnace.” 2010. Masters Thesis, California State University – Sacramento. Accessed November 19, 2017. http://hdl.handle.net/10211.9/834.

MLA Handbook (7th Edition):

Sirinonrang, Sukanya. “On-line measurements using neural networks and soft computing for the control of glass production furnace.” 2010. Web. 19 Nov 2017.

Vancouver:

Sirinonrang S. On-line measurements using neural networks and soft computing for the control of glass production furnace. [Internet] [Masters thesis]. California State University – Sacramento; 2010. [cited 2017 Nov 19]. Available from: http://hdl.handle.net/10211.9/834.

Council of Science Editors:

Sirinonrang S. On-line measurements using neural networks and soft computing for the control of glass production furnace. [Masters Thesis]. California State University – Sacramento; 2010. Available from: http://hdl.handle.net/10211.9/834


Oregon State University

27. Moore, Christopher (Chistopher Emory). A recurrent neural network implementation using the graphics processing unit.

Degree: MS, Computer Science, 2009, Oregon State University

 We took the back-propagation algorithms of Werbos for recurrent and feed-forward neural networks and implemented them on machines with graphics processing units (GPU). The parallelism… (more)

Subjects/Keywords: rnn; Neural networks (Computer science)

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APA (6th Edition):

Moore, C. (. E. (2009). A recurrent neural network implementation using the graphics processing unit. (Masters Thesis). Oregon State University. Retrieved from http://hdl.handle.net/1957/13658

Chicago Manual of Style (16th Edition):

Moore, Christopher (Chistopher Emory). “A recurrent neural network implementation using the graphics processing unit.” 2009. Masters Thesis, Oregon State University. Accessed November 19, 2017. http://hdl.handle.net/1957/13658.

MLA Handbook (7th Edition):

Moore, Christopher (Chistopher Emory). “A recurrent neural network implementation using the graphics processing unit.” 2009. Web. 19 Nov 2017.

Vancouver:

Moore C(E. A recurrent neural network implementation using the graphics processing unit. [Internet] [Masters thesis]. Oregon State University; 2009. [cited 2017 Nov 19]. Available from: http://hdl.handle.net/1957/13658.

Council of Science Editors:

Moore C(E. A recurrent neural network implementation using the graphics processing unit. [Masters Thesis]. Oregon State University; 2009. Available from: http://hdl.handle.net/1957/13658


University of Johannesburg

28. Lourens, Cecil Albert. Recurrent neural networks in the chemical process industries .

Degree: 2012, University of Johannesburg

 This dissertation discusses the results of a literature survey into the theoretical aspects and development of recurrent neural networks. In particular, the various architectures and… (more)

Subjects/Keywords: Neural networks (Computer science)

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APA (6th Edition):

Lourens, C. A. (2012). Recurrent neural networks in the chemical process industries . (Thesis). University of Johannesburg. Retrieved from http://hdl.handle.net/10210/6913

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):

Lourens, Cecil Albert. “Recurrent neural networks in the chemical process industries .” 2012. Thesis, University of Johannesburg. Accessed November 19, 2017. http://hdl.handle.net/10210/6913.

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

MLA Handbook (7th Edition):

Lourens, Cecil Albert. “Recurrent neural networks in the chemical process industries .” 2012. Web. 19 Nov 2017.

Vancouver:

Lourens CA. Recurrent neural networks in the chemical process industries . [Internet] [Thesis]. University of Johannesburg; 2012. [cited 2017 Nov 19]. Available from: http://hdl.handle.net/10210/6913.

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

Council of Science Editors:

Lourens CA. Recurrent neural networks in the chemical process industries . [Thesis]. University of Johannesburg; 2012. Available from: http://hdl.handle.net/10210/6913

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


University of Toronto

29. Burianova', Hana. Exploration of Autobiographical, Episodic, and Semantic Memory: Modeling of a Common Neural Network.

Degree: 2009, University of Toronto

The purpose of this thesis was to delineate the neural underpinning of three types of declarative memory retrieval; autobiographical, episodic, and semantic. Autobiographical memory was… (more)

Subjects/Keywords: declarative memory; neural networks; 0633

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APA (6th Edition):

Burianova', H. (2009). Exploration of Autobiographical, Episodic, and Semantic Memory: Modeling of a Common Neural Network. (Doctoral Dissertation). University of Toronto. Retrieved from http://hdl.handle.net/1807/17456

Chicago Manual of Style (16th Edition):

Burianova', Hana. “Exploration of Autobiographical, Episodic, and Semantic Memory: Modeling of a Common Neural Network.” 2009. Doctoral Dissertation, University of Toronto. Accessed November 19, 2017. http://hdl.handle.net/1807/17456.

MLA Handbook (7th Edition):

Burianova', Hana. “Exploration of Autobiographical, Episodic, and Semantic Memory: Modeling of a Common Neural Network.” 2009. Web. 19 Nov 2017.

Vancouver:

Burianova' H. Exploration of Autobiographical, Episodic, and Semantic Memory: Modeling of a Common Neural Network. [Internet] [Doctoral dissertation]. University of Toronto; 2009. [cited 2017 Nov 19]. Available from: http://hdl.handle.net/1807/17456.

Council of Science Editors:

Burianova' H. Exploration of Autobiographical, Episodic, and Semantic Memory: Modeling of a Common Neural Network. [Doctoral Dissertation]. University of Toronto; 2009. Available from: http://hdl.handle.net/1807/17456

30. Triastuti Sugiyarto, Endang. Analysing rounding data using radial basis function neural networks model.

Degree: PhD, 2007, University of Northampton

 Unspecified counting practices used in a data collection may create rounding to certain ‘based’ number that can have serious consequences on data quality. Statistical methods… (more)

Subjects/Keywords: 600; QA76.87 Neural networks

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APA (6th Edition):

Triastuti Sugiyarto, E. (2007). Analysing rounding data using radial basis function neural networks model. (Doctoral Dissertation). University of Northampton. Retrieved from http://nectar.northampton.ac.uk/2809/ ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.545825

Chicago Manual of Style (16th Edition):

Triastuti Sugiyarto, Endang. “Analysing rounding data using radial basis function neural networks model.” 2007. Doctoral Dissertation, University of Northampton. Accessed November 19, 2017. http://nectar.northampton.ac.uk/2809/ ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.545825.

MLA Handbook (7th Edition):

Triastuti Sugiyarto, Endang. “Analysing rounding data using radial basis function neural networks model.” 2007. Web. 19 Nov 2017.

Vancouver:

Triastuti Sugiyarto E. Analysing rounding data using radial basis function neural networks model. [Internet] [Doctoral dissertation]. University of Northampton; 2007. [cited 2017 Nov 19]. Available from: http://nectar.northampton.ac.uk/2809/ ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.545825.

Council of Science Editors:

Triastuti Sugiyarto E. Analysing rounding data using radial basis function neural networks model. [Doctoral Dissertation]. University of Northampton; 2007. Available from: http://nectar.northampton.ac.uk/2809/ ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.545825

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