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Book Cover
E-book
Author Ansari, Mohd. Samar, author

Title Non-linear feedback neural networks : VLSI implementations and applications / Mohd. Samar Ansari
Published New Delhi : Springer, [2013?]
©2014

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Description 1 online resource (xxii, 201 pages) : illustrations
Series Studies in Computational Intelligence, 1860-949X ; v. 508
Studies in computational intelligence ; v. 508.
Contents Voltage-mode Neural Network for the Solution of Linear Equations -- Mixed-mode Neural Circuit for Solving Linear Equations -- Non-Linear Feedback Neural Circuits for Linear and Quadratic Programming -- OTA-based Implementations of Mixed-mode Neural Circuits -- Appendix A: Mixed-mode Neural Network for Graph Colouring -- Appendix B: Mixed-mode Neural Network for Ranking
Summary 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
Analysis wiskundige modellen
mathematical models
neurale netwerken
neural networks
engineering
circuits
computational science
elektronica
electronics
instrumentatie
instrumentation
Engineering (General)
Techniek (algemeen)
Bibliography Includes bibliographical references
Notes Online resource; title from PDF title page (SpringerLink, viewed September 9, 2013)
Subject Neural networks (Computer science)
Feedback control systems.
Integrated circuits -- Very large scale integration.
Neural Networks, Computer
Ingénierie.
Feedback control systems
Integrated circuits -- Very large scale integration
Neural networks (Computer science)
Form Electronic book
ISBN 9788132215639
813221563X