Non-Linear Feedback Neural Networks VLSI Implementations and Applications /

This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog computation. It is well known that the standard HNN suffers from problems of convergence to local minima, and requirement of a large number of neurons and synaptic weights. Therefore, improved soluti...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Ansari, Mohd. Samar (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New Delhi : Springer India : Imprint: Springer, 2014.
Edición:1st ed. 2014.
Colección:Studies in Computational Intelligence, 508
Temas:
Computational intelligence.
Electronic circuits.
Neural networks (Computer science) .
Electronics.
Computational Intelligence.
Electronic Circuits and Systems.
Mathematical Models of Cognitive Processes and Neural Networks.
Electronics and Microelectronics, Instrumentation.
Acceso en línea:Texto Completo
Descripción
Sumario:This book aims to present a viable alternative to the Hopfield Neural Network (HNN) model for analog computation. It is well known that the standard HNN suffers from problems of convergence to local minima, and requirement of a large number of neurons and synaptic weights. Therefore, improved solutions are needed. The non-linear synapse neural network (NoSyNN) is one such possibility and is discussed in detail in this book. This book also discusses the applications in computationally intensive tasks like graph coloring, ranking, and linear as well as quadratic programming. The material in the book is useful to students, researchers and academician working in the area of analog computation.
Descripción Física:XXII, 201 p. 79 illus. online resource.
ISBN:9788132215639
ISSN:1860-9503 ;

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