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Discrete Neural Computation

1995 Computers
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Release : 1995
Genre : Computers
Kind : eBook
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Book Synopsis Discrete Neural Computation by : Kai-Yeung Siu

Download or read book Discrete Neural Computation written by Kai-Yeung Siu. This book was released on 1995. Available in PDF, EPUB and Kindle. Book excerpt: Written by the three leading authorities in the field, this book brings together -- in one volume -- the recent developments in discrete neural computation, with a focus on neural networks with discrete inputs and outputs. It integrates a variety of important ideas and analytical techniques, and establishes a theoretical foundation for discrete neural computation. Discusses the basic models for discrete neural computation and the fundamental concepts in computational complexity; establishes efficient designs of threshold circuits for computing various functions; develops techniques for analyzing the computational power of neural models. A reference/text for computer scientists and researchers involved with neural computation and related disciplines.

Discrete Mathematics of Neural Networks

2001-01-01 Computers
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Release : 2001-01-01
Genre : Computers
Kind : eBook
Book Rating : 80X/5 ( reviews)

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Book Synopsis Discrete Mathematics of Neural Networks by : Martin Anthony

Download or read book Discrete Mathematics of Neural Networks written by Martin Anthony. This book was released on 2001-01-01. Available in PDF, EPUB and Kindle. Book excerpt: This concise, readable book provides a sampling of the very large, active, and expanding field of artificial neural network theory. It considers select areas of discrete mathematics linking combinatorics and the theory of the simplest types of artificial neural networks. Neural networks have emerged as a key technology in many fields of application, and an understanding of the theories concerning what such systems can and cannot do is essential. Some classical results are presented with accessible proofs, together with some more recent perspectives, such as those obtained by considering decision lists. In addition, probabilistic models of neural network learning are discussed. Graph theory, some partially ordered set theory, computational complexity, and discrete probability are among the mathematical topics involved. Pointers to further reading and an extensive bibliography make this book a good starting point for research in discrete mathematics and neural networks.

Discrete-Time High Order Neural Control

2008-06-24 Technology & Engineering
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Release : 2008-06-24
Genre : Technology & Engineering
Kind : eBook
Book Rating : 893/5 ( reviews)

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Book Synopsis Discrete-Time High Order Neural Control by : Edgar N. Sanchez

Download or read book Discrete-Time High Order Neural Control written by Edgar N. Sanchez. This book was released on 2008-06-24. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks have become a well-established methodology as exempli?ed by their applications to identi?cation and control of general nonlinear and complex systems; the use of high order neural networks for modeling and learning has recently increased. Usingneuralnetworks,controlalgorithmscanbedevelopedtoberobustto uncertainties and modeling errors. The most used NN structures are Feedf- ward networks and Recurrent networks. The latter type o?ers a better suited tool to model and control of nonlinear systems. There exist di?erent training algorithms for neural networks, which, h- ever, normally encounter some technical problems such as local minima, slow learning, and high sensitivity to initial conditions, among others. As a viable alternative, new training algorithms, for example, those based on Kalman ?ltering, have been proposed. There already exists publications about trajectory tracking using neural networks; however, most of those works were developed for continuous-time systems. On the other hand, while extensive literature is available for linear discrete-timecontrolsystem,nonlineardiscrete-timecontroldesigntechniques have not been discussed to the same degree. Besides, discrete-time neural networks are better ?tted for real-time implementations.

Efficient gradient computation for continuous and discrete time-dependent neural networks

1991
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Release : 1991
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Book Synopsis Efficient gradient computation for continuous and discrete time-dependent neural networks by : Stefan Miesbach

Download or read book Efficient gradient computation for continuous and discrete time-dependent neural networks written by Stefan Miesbach. This book was released on 1991. Available in PDF, EPUB and Kindle. Book excerpt:

Neural Networks and Analog Computation

2012-12-06 Computers
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Release : 2012-12-06
Genre : Computers
Kind : eBook
Book Rating : 07X/5 ( reviews)

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Book Synopsis Neural Networks and Analog Computation by : Hava T. Siegelmann

Download or read book Neural Networks and Analog Computation written by Hava T. Siegelmann. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: 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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