Neural Networks and Their Implementation
Biological inspiration, historical background, learning in neural nets (backpropagation, hebian, etc.), single- and multi-layer networks, associative memories, classification and clustering models, recurrent networks. Neural network technology, implementation software and hardware technologies, algorithm definitions, computational requirements, solution methods, parallel processing hardware. VLSI and optical implementations of neural networks.
Graduate course in the Electrical Engineering program offered by the Faculty of Graduate Studies.