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Neural Networks and Analog Computation : Beyond the Turing Limit
by Hava Siegelman and Siegelman

Overview -

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.  Read more...


 
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More About Neural Networks and Analog Computation by Hava Siegelman; Siegelman
 
 
 
Overview

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 theory of computation but also explicated the computational complexity associated with biological networks, adaptive engineering tools, and related models from the fields of control theory and nonlinear dynamics. The material in this book will be of interest to researchers in a variety of engineering and applied sciences disciplines. In addition, the work may provide the base of a graduate-level seminar in neural networks for computer science students.


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Details
  • ISBN-13: 9780817639495
  • ISBN-10: 0817639497
  • Publisher: Birkhauser
  • Publish Date: December 1998
  • Page Count: 181

Series: Progress in Theoretical Computer Science

Related Categories

Books > Computers & Internet > Neural Networks
Books > Computers & Internet > Intelligence (AI) & Semantics
Books > Science > Physics - Mathematical & Computational

 
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