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Detalles bibliogr�ficos

T�tulo: Fundamentals of Artificial Neural Networks
Editor: Mit Pr
Fecha de publicaci�n: 1995
Idioma: Ingl�s
ISBN 10: 026208239X
ISBN 13: 9780262082396
Encuadernaci�n: Encuadernaci�n de tapa dura
Estado: Good

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Sinopsis

As book review editor of the IEEE Transactions on Neural Networks, Mohamad Hassoun has had the opportunity to assess the multitude of books on artificial neural networks that have appeared in recent years. Now, in Fundamentals of Artificial Neural Networks, he provides the first systematic account of artificial neural network paradigms by identifying clearly the fundamental concepts and major methodologies underlying most of the current theory and practice employed by neural network researchers.

Such a systematic and unified treatment, although sadly lacking in most recent texts on neural networks, makes the subject more accessible to students and practitioners. Here, important results are integrated in order to more fully explain a wide range of existing empirical observations and commonly used heuristics. There are numerous illustrative examples, over 200 end-of-chapter analytical and computer-based problems that will aid in the development of neural network analysis and design skills, and a bibliography of nearly 700 references.

Proceeding in a clear and logical fashion, the first two chapters present the basic building blocks and concepts of artificial neural networks and analyze the computational capabilities of the basic network architectures involved. Supervised, reinforcement, and unsupervised learning rules in simple nets are brought together in a common framework in chapter three. The convergence and solution properties of these learning rules are then treated mathematically in chapter four, using the "average learning equation" analysis approach. This organization of material makes it natural to switch into learning multilayer nets using backprop and its variants, described in chapter five. Chapter six covers most of the major neural network paradigms, while associative memories and energy minimizing nets are given detailed coverage in the next chapter. The final chapter takes up Boltzmann machines and Boltzmann learning along with other global search/optimization algorithms such as stochastic gradient search, simulated annealing, and genetic algorithms.

Rese�a del editor

This text provides a systematic account of artificial neural network paradigms by identifying the fundamental concepts and major methodologies underlying most of the current theory and practice employed by neural network researchers. The aim of such a systematic and unified treatment is to make the subject more accessible to students and practitioners. Important results are integrated in order to explain a wide range of existing empirical observations and commonly used heuristics. There are numerous illustrative examples, over 200 end-of-chapter analytical and computer-based problems that will aid in the development of neural network analysis and design skills, and a bibliography of nearly 700 references. The first two chapters present the basic concepts of artificial neural networks and analyze the computational capabilities of the basic network architectures involved. Supervised, reinforcement and unsupervised learning rules in simple nets are brought together in a common framework in Chapter Three. The convergence and solution properties of these learning rules are then examined in Chapter Four, using the "average learning equation" analysis approach. Learning multilayer nets are described in Chapter Five whilst Chapter Six covers neural network paradigms and associative memories and energy minimizing nets are considered in the next chapter. The final chapter takes up Boltzmann machines and Boltzmann learning along with other global search/optimization algorithms.

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Phatpocket Limited is a world class secondhand bookstore located in the Hertfordshire countryside in the United Kingdom. We specialize in textbooks across an enormous variety of subjects. We aim to provide a low cost source of high quality textbooks to the academic community. We also have a sizable collection of rare and collectible books. We are dedicated to providing our customers with the highest standard of customer service in the bookselling business.Phatpocket Limited is registered in England and Wales: No. 04924751.

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