[PDF.04be] Neural Networks and Analog Computation: Beyond the Turing Limit (Progress in Theoretical Computer Science)

Neural Networks and Analog Computation: Beyond the Turing Limit (Progress in Theoretical Computer Science)

[PDF.pf38] Neural Networks and Analog Computation: Beyond the Turing Limit (Progress in Theoretical Computer Science)

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 | #3084784 in Books |  Birkhäuser |  1998-12-01 | Original language:English | PDF # 1 |  9.21 x.50 x6.14l,1.00 | File type: PDF | 181 pages

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||5 of 5 people found the following review helpful.| Elegant theoretical apparatus|By Erez Lieberman Aiden|This book provides a systematic overview of a beautiful theoretical apparatus that the author and collaborators have developed for describing the computational power of neural networks. It addresses neural networks from the standpoint of computational complexity theory, not machine learning.

A central issue that a| ||"All of the three primary questions are considered: What computational models can the net simulate (within polynomial bounds)? What are the computational complexity classes that are relevant to the net? How does the net (which, after all, is an analog device)

The theoretical foundations of Neural Networks and Analog Computation conceptualize neural networks as a particular type of computer consisting of multiple assemblies of basic processors interconnected in an intricate structure. Examining these networks under various resource constraints reveals a continuum of computational devices, several of which coincide with well-known classical models. On a mathematical level, the treatment of neural computations enriches the th...

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