Neural Networks and Analog Computation

Name: Neural Networks and Analog Computation
Brand: Springer, Basel
SKU: 9780817639495
Price: 63556 HUF
Availability: InStock

Beyond the Turing Limit

Szerző: Hava T. Siegelmann

Nyelv:

Kötés: Kemény kötésű

Kiadó: Springer, Basel

Elérhetőség: Beszállítói készleten alacsony példányszámban

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The theoretical foundations of Neural Networks and Analog Computation conceptualize neural networks...

Információk a könyvről

Szerző

Hava T. Siegelmann

Nyelv

Angol

Kötés

Könyv - Kemény kötésű

Kiadva

1998

oldal

181

EAN

9780817639495

ISBN

0817639497

Enbook ID

01399156

Kiadó

Springer, Basel

Súly

467

Méretek

161 x 240 x 12

Teljes leírás

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. What emerges is a Church-Turing-like thesis, applied to the field of analog computation, which features the neural network model in place of the digital Turing machine. This new concept can serve as a point of departure for the development of alternative, supra-Turing, computational theories. 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 topics covered in this work will appeal to a wide readership from a variety of disciplines. Special care has been taken to explain the theory clearly and concisely. The first chapter review s the fundamental terms of modern computational theory from the point of view of neural networks and serves as a reference for the remainder of the book. Each of the subsequent chapters opens with introductory material and proceeds to explain the chapter s connection to the development of the theory. Thereafter, the concept is defined in mathematical terms.§Although the notion of a neural network essentially arises from biology, many engineering applications have been found through highly idealized and simplified models of neuron behavior. Particular areas of application have been as diverse as explosives detection in airport security, signature verification, financial and medical times series prediction, vision, speech processing, robotics, nonlinear control, and signal processing. The focus in all of these models is entirely on the behavior of networks as computer.§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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Neural Networks and Analog Computation

Beyond the Turing Limit

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