Description
Principles of neural networks. Basic neurophysiology, neural nets as finite-state machines, synaptic learning, perceptrons, the LMS and back propagation algorithms, capacity theorems, feedforward nets as statistical classifiers, stability of feedback nets, self-organizing feature maps, adaptive resonance theory, retinal and cochlear models.
Prerequisite: EE 210.
Grading
Normal Grade Rules
Units
3
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