9.641J / 8.594J Introduction to Neural Networks, Fall 2002

9.641J / 8.594J Introduction to Neural Networks, Fall 2002

Organization of synaptic connectivity as the basis of neural computation and learning. Single and multilayer perceptrons. Dynamical theories of recurrent networks: amplifiers, attractors, and hybrid computation. Backpropagation and Hebbian learning. Models of perception, motor control, memory, and n...

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Bibliographic Details
Main Author: Seung, H. Sebastian
Other Authors: Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Format: Learning Object
Language:en-US
Published: 2002
Subjects:
synaptic connectivity
computation
learning
multilayer perceptrons
recurrent networks
amplifiers
attractors
hybrid computation
Backpropagation
Hebbian learning
perception
motor control
memory
neural development
9.641J
8.594J
9.641
8.594
Neural networks (Computer science)
Online Access:http://hdl.handle.net/1721.1/36327

Internet

http://hdl.handle.net/1721.1/36327

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