Abu-Mostafa, Yaser S. (1989) Information theory, complexity and neural networks. IEEE Communications Magazine, 27 (11). 25-28, 82. ISSN 0163-6804 http://resolver.caltech.edu/CaltechAUTHORS:ABUieeecm89
See Usage Policy.
Use this Persistent URL to link to this item: http://resolver.caltech.edu/CaltechAUTHORS:ABUieeecm89
Some of the main results in the mathematical evaluation of neural networks as information processing systems are discussed. The basic operation of feedback and feed-forward neural networks is described. Their memory capacity and computing power are considered. The concept of learning by example as it applies to neural networks is examined.
|Additional Information:||“©1989 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”|
|Usage Policy:||No commercial reproduction, distribution, display or performance rights in this work are provided.|
|Deposited By:||Archive Administrator|
|Deposited On:||16 May 2005|
|Last Modified:||26 Dec 2012 08:39|
Repository Staff Only: item control page