Neural Networks and Analog Computation: Beyond the Turing Limit (Progress in Theoretical Computer Science)
| Author | : | |
| Rating | : | 4.42 (722 Votes) |
| Asin | : | 0817639497 |
| Format Type | : | paperback |
| Number of Pages | : | 181 Pages |
| Publish Date | : | 2013-12-17 |
| Language | : | English |
DESCRIPTION:
42, No 3.. "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) relate to Church’s thesis? Moreover the power of the basic model is also analyzed when the domain of reals is replaced by the rationals and the integers." Mathematical Reviews"Siegelmann's book focuses on the computational complexities of neural networks and making this research accessiblethe book accomplishes the said task nicely."---S
Elegant theoretical apparatus 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 arises is what va. Discussion of the consequences, not the original proof N. Hockings Skeptics wanting to see the original proof, and how such "machines" can exist as natural phenomena within the constraints of physics, should refer to the author's peer reviewed articlesH.T. Siegelmann, "Computation Beyond the Turing Limit," Science, 238(28), April 1995: 632-637andH.T. Siegelmann, "Analog Computational Power" Sci. J. Felix Costa said Hypercomputation in the limits of classical physical reality. A computer is an artifact. Through specific control mechanisms of electric currents it was possible to domesticate natural phenomena, and put them at men service, giving rise to the levels of automation that characterize the world in the turning of the millennium. But a computer is an analog artifact. Paul Cull, from Oregon Stat
In addition, the work may provide the base of a graduate-level seminar in neural networks for computer science students.. The material in this book will be of interest to researchers in a variety of engineering and applied sciences disciplines. Examining these networks under various resource constraints reveals a continuum of computational devices, several of which coincide with well-known classical models. 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. On a mathematical level, the treatment of neural computations enriches the theory of computation but also explicated the computational complexity associated with biological n