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Survival pattern of transplanted stem cellsWong, Wing-ki, Shirley, 黃穎琪 January 2005 (has links)
published_or_final_version / Medical Sciences / Master / Master of Medical Sciences
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Imaging synaptic activity of neuronal networks in vitro and in vivo using a fluorescent calcium indicatorDreosti, Elena January 2010 (has links)
No description available.
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Toward a formalism for the automation of neural network construction and processing controlCzuchry, Andrew J., Jr. 08 1900 (has links)
No description available.
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Neural network vector quantizer image compressor trained with genetic algorithmsFain, E. John 05 1900 (has links)
No description available.
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On the performance issues of the bidirectional associative memoryBragansa, John 05 1900 (has links)
No description available.
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Multistability in bursting patterns in a model of a multifunctional central pattern generatorBrooks, Matthew Bryan. January 2009 (has links)
Thesis (M.S.)--Georgia State University, 2009. / Title from title page (Digital Archive@GSU, viewed July 20, 2010) Andrey Shilnikov, Robert Clewley, Gennady Cymbalyuk, committee co-chairs; Igor Belykh, Vladimir Bondarenko, Mukesh Dhamala, Michael Stewart, committee members. Includes bibliographical references (p. 65-67).
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Survival pattern of transplanted stem cells /Wong, Wing-ki, Shirley. January 2005 (has links)
Thesis (M. Med. Sc.)--University of Hong Kong, 2005.
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Irregular behavior in an excitatory-inhibitory networkPark, Choongseok, January 2007 (has links)
Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 144-147).
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An incremental learning system for artificial neural networksDe Wet, Anton Petrus Christiaan 11 September 2014 (has links)
M.Ing. (Electrical And Electronic Engineering) / 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 algorithms such as back propagation. It is argued that incremental learning is fundamental to the adaptive learning behavior observed in human intelligence and constitutes an imperative step towards artificial cognition. The importance of developing incremental learning as a system of ANNs is stressed before the complete system is presented. Details of the development and implementation of the system is complemented by the description of two case studies. In conclusion the role of the incremental learning system as basis for further development of fundamental elements of cognition is projected.
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Connectionist rule processing using recursive auto-associative memorySt Aubyn, Michael January 2001 (has links)
No description available.
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