Non-Linear Feedback Neural Networks (Record no. 53334)

000 -LEADER
fixed length control field 02939nam a22005295i 4500
001 - CONTROL NUMBER
control field 978-81-322-1563-9
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200420221303.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 130902s2014 ii | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9788132215639
-- 978-81-322-1563-9
082 04 - CLASSIFICATION NUMBER
Call Number 006.3
100 1# - AUTHOR NAME
Author Ansari, Mohd. Samar.
245 10 - TITLE STATEMENT
Title Non-Linear Feedback Neural Networks
Sub Title VLSI Implementations and Applications /
300 ## - PHYSICAL DESCRIPTION
Number of Pages XXII, 201 p. 79 illus.
490 1# - SERIES STATEMENT
Series statement Studies in Computational Intelligence,
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Introduction -- Background -- 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.
520 ## - SUMMARY, ETC.
Summary, etc 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.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-81-322-1563-9
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- New Delhi :
-- Springer India :
-- Imprint: Springer,
-- 2014.
336 ## -
-- text
-- txt
-- rdacontent
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-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Neural networks (Computer science).
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational intelligence.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electronics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Microelectronics.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electronic circuits.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computational Intelligence.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Circuits and Systems.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Mathematical Models of Cognitive Processes and Neural Networks.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electronics and Microelectronics, Instrumentation.
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
-- 1860-949X ;
912 ## -
-- ZDB-2-ENG

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