| dc.contributor.author | Seung, H. Sebastian | en_US |
| dc.coverage.temporal | Fall 2002 | en_US |
| dc.date.issued | 2002-12 | |
| dc.identifier | 9.641J-Fall2002 | |
| dc.identifier | local: 9.641J | |
| dc.identifier | local: 8.594J | |
| dc.identifier | local: IMSCP-MD5-bd6878f7d57a228449535604255a526a | |
| dc.identifier.uri | http://hdl.handle.net/1721.1/36327 | |
| dc.description.abstract | 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 neural development. Alternate years. | en_US |
| dc.language | en-US | en_US |
| dc.rights.uri | Usage Restrictions: This site (c) Massachusetts Institute of Technology 2003. Content within individual courses is (c) by the individual authors unless otherwise noted. The Massachusetts Institute of Technology is providing this Work (as defined below) under the terms of this Creative Commons public license ("CCPL" or "license"). The Work is protected by copyright and/or other applicable law. Any use of the work other than as authorized under this license is prohibited. By exercising any of the rights to the Work provided here, You (as defined below) accept and agree to be bound by the terms of this license. The Licensor, the Massachusetts Institute of Technology, grants You the rights contained here in consideration of Your acceptance of such terms and conditions. | en_US |
| dc.subject | synaptic connectivity | en_US |
| dc.subject | computation | en_US |
| dc.subject | learning | en_US |
| dc.subject | multilayer perceptrons | en_US |
| dc.subject | recurrent networks | en_US |
| dc.subject | amplifiers | en_US |
| dc.subject | attractors | en_US |
| dc.subject | hybrid computation | en_US |
| dc.subject | Backpropagation | en_US |
| dc.subject | Hebbian learning | en_US |
| dc.subject | perception | en_US |
| dc.subject | motor control | en_US |
| dc.subject | memory | en_US |
| dc.subject | neural development | en_US |
| dc.subject | 9.641J | en_US |
| dc.subject | 8.594J | en_US |
| dc.subject | 9.641 | en_US |
| dc.subject | 8.594 | en_US |
| dc.subject | Neural networks (Computer science) | en_US |
| dc.title | 9.641J / 8.594J Introduction to Neural Networks, Fall 2002 | en_US |
| dc.title.alternative | Introduction to Neural Networks | en_US |
