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Harmonic analysis of neural networks

Bruck, Jehoshua (1989) Harmonic analysis of neural networks. In: Twenty-Third Asilomar Conference on Signals, Systems and Computers. Maple Press , San Jose, CA, pp. 142-146. ISBN 0-929029-30-1

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Neural networks models have attracted a lot of interest in recent years mainly because there were perceived as a new idea for computing. These models can be described as a network in which every node computes a linear threshold function. One of the main difficulties in analyzing the properties of these networks is the fact that they consist of nonlinear elements. I will present a novel approach, based on harmonic analysis of Boolean functions, to analyze neural networks. In particular I will show how this technique can be applied to answer the following two fundamental questions (i) what is the computational power of a polynomial threshold element with respect to linear threshold elements? (ii) Is it possible to get exponentially many spurious memories when we use the outer-product method for programming the Hopfield model?

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Additional Information:© 1989 Maple Press. Date of Current Version: 28 May 2003.
Record Number:CaltechAUTHORS:20120524-090912809
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Official Citation:Bruck, J.; , "Harmonic analysis of neural networks," Signals, Systems and Computers, 1989. Twenty-Third Asilomar Conference on , vol.1, no., pp. 142- 146, 1989 doi: 10.1109/ACSSC.1989.1200767 URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:31627
Deposited By: Tony Diaz
Deposited On:06 Jun 2012 17:57
Last Modified:26 Dec 2012 15:15

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