Neural networks are program and memory at once, useful where traditional techniques fail, i.e., for artificial speech and image recognition. Emphasis on existing and emerging engineering applications. Parallel distributed processing, Hebb's rule, Hopfield net, back-propagation algorithm, perceptrons, unsupervised learning, Kohenen self-organizing map, genetic algorithms, neocognitron, adaline. Illustrated with computer programs and lectures.
Spring | Summer | Fall | ||
---|---|---|---|---|
(Session 1) | (Session 2) | |||
2023 | ||||
2022 | ||||
2021 | ||||
2020 | ||||
2019 | ||||
2018 | ||||
2017 | ||||
2016 | ||||
2015 | ||||
2014 | ||||
2013 | ||||
2012 | ||||
2011 | ||||
2010 | ||||
2009 | ||||
2008 | ||||
2007 | ||||
2006 | ||||
2005 | ||||
2004 | ||||
2003 | ||||
2002 |
Intro. To Neural Networks (3c)
|
|||
2001 | ||||
2000 | ||||
1999 | ||||
1998 |