Dong, Dawei (1991) Dynamic properties of neural networks. Dissertation (Ph.D.), California Institute of Technology. http://resolver.caltech.edu/CaltechETD:etd-06202007-092922
Two kinds of dynamic processes take place in neural networks. One involves the change with time of the activity of each neuron. The other involves the change in strength of the connections (synapses) between neurons. When a neural network is learning or developing, both processes simultaneously take place, and their dynamics interact. This interaction is particularly important in feedback networks. A Lyapunov function is developed to help understand the combined activity and synapse dynamics for a class of such adaptive networks. The methods and viewpoint are illustrated by using them to describe the development of orientation selective cells in cat primary visual cortex. Within this model, orientation selectivity originates from feedback pathways within an area of cortex, rather than feedforward pathways between areas.
|Item Type:||Thesis (Dissertation (Ph.D.))|
|Degree Grantor:||California Institute of Technology|
|Division:||Physics, Mathematics and Astronomy|
|Thesis Availability:||Restricted to Caltech community only|
|Defense Date:||15 April 1991|
|Default Usage Policy:||No commercial reproduction, distribution, display or performance rights in this work are provided.|
|Deposited By:||Imported from ETD-db|
|Deposited On:||13 Jul 2007|
|Last Modified:||26 Dec 2012 02:53|
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