Neural networks and learning machines / (Record no. 16665)

MARC details
000 -LEADER
fixed length control field 02102nam a2200241Ia 4500
003 - CONTROL NUMBER IDENTIFIER
control field NULRC
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250520102834.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250520s9999 xx 000 0 und d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9780131471399
040 ## - CATALOGING SOURCE
Transcribing agency NULRC
050 ## - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA 76.87 .H39 2009
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Haykin, Simon.
Relator term author
245 #0 - TITLE STATEMENT
Title Neural networks and learning machines /
Statement of responsibility, etc. Simon Haykin
250 ## - EDITION STATEMENT
Edition statement 3rd edition
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. New York :
Name of publisher, distributor, etc. Prentice Hall/Pearson,
Date of publication, distribution, etc. c2009
300 ## - PHYSICAL DESCRIPTION
Extent xxx, 906 pages :
Other physical details color illustrations ;
Dimensions 24 cm.
365 ## - TRADE PRICE
Price amount PHP11522.6
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc. note Includes bibliographical references (pages 847-887) and index.
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note Preface-Introduction -- Chapter 1: Rosenblatt's Perceptron -- Chapter 2: Model Building through Regression-Chapter 3-The Least-Mean-Square-Algorithm -- Chapter 4 Multilayer Perceptrons-Chapter 5: Kernal Merhods and Radial Basis Function Networks -- Chapter 6 Support Vector Machines -- Chapter 7 Regularization Theory -- Chapter 8 Principal-Components Analysis -- Chapter 9 Self-Organizing Maps -- Chapter 10 Information-Theoretic Learning Models -- Chapter 11 Stochastic Methods Rooted in Statistical Mechanics -- Chapter 12 Dynamic Programming -- Chapter 13 Neurodynamics -- Chapter 14 Bayseian Filtering for State Estimation of Dynamic Systems -- Chapter 15 Dynamically Driven Recurrent Networks -Bibliography -- Index 889.
520 ## - SUMMARY, ETC.
Summary, etc. Neural Networks and Learning Machines, Third Edition is renowned for its thoroughness and readability. This well-organized and completely up-to-date text remains the most comprehensive treatment of neural networks from an engineering perspective. This is ideal for professional engineers and research scientists. Refocused, revised and renamed to reflect the duality of neural networks and learning machines, this edition recognizes that the subject matter is richer when these topics are studied together. Ideas drawn from neural networks and machine learning are hybridized to perform improved learning tasks beyond the capability of either independently.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element NEURAL NETWORKS (COMPUTER SCIENCE)
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Library of Congress Classification
Koha item type Books
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection Home library Current library Shelving location Date acquired Source of acquisition Cost, normal purchase price Total checkouts Full call number Barcode Date last seen Copy number Price effective from Koha item type
    Library of Congress Classification     Gen. Ed. - CCIT LRC - Main National University - Manila General Circulation 02/21/2018 Purchased - Amazon 11522.60   GC QA 76.87 .H39 2009 NULIB000014424 05/20/2025 c.1 05/20/2025 Books