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. https://resolver.caltech.edu/CaltechAUTHORS:20120524-090912809
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Abstract
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?
| Item Type: | Book Section | |||||||||
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| Additional Information: | © 1989 Maple Press. Date of Current Version: 28 May 2003. | |||||||||
| DOI: | 10.1109/ACSSC.1989.1200767 | |||||||||
| Record Number: | CaltechAUTHORS:20120524-090912809 | |||||||||
| Persistent URL: | https://resolver.caltech.edu/CaltechAUTHORS:20120524-090912809 | |||||||||
| 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: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1200767&isnumber=27032 | |||||||||
| Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | |||||||||
| ID Code: | 31627 | |||||||||
| Collection: | CaltechAUTHORS | |||||||||
| Deposited By: | Tony Diaz | |||||||||
| Deposited On: | 06 Jun 2012 17:57 | |||||||||
| Last Modified: | 09 Nov 2021 19:57 |
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