MARC details
000 -LEADER |
fixed length control field |
03918nam a22004815i 4500 |
001 - CONTROL NUMBER |
control field |
978-3-540-85130-1 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
DE-He213 |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20170628034904.0 |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
fixed length control field |
cr nn 008mamaa |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
100301s2009 gw | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9783540851301 |
-- |
978-3-540-85130-1 |
024 7# - OTHER STANDARD IDENTIFIER |
Standard number or code |
10.1007/978-3-540-85130-1 |
Source of number or code |
doi |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
Classification number |
TA329-348 |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
Classification number |
TA640-643 |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
TBJ |
Source |
bicssc |
072 #7 - SUBJECT CATEGORY CODE |
Subject category code |
MAT003000 |
Source |
bisacsh |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
519 |
Edition number |
23 |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
David, Vasantha Kalyani. |
Relator term |
author. |
245 10 - TITLE STATEMENT |
Title |
Pattern Recognition using Neural and Functional Networks |
Medium |
[electronic resource] / |
Statement of responsibility, etc |
by Vasantha Kalyani David, Sundaramoorthy Rajasekaran. |
264 #1 - |
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Berlin, Heidelberg : |
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Springer Berlin Heidelberg, |
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2009. |
300 ## - PHYSICAL DESCRIPTION |
Other physical details |
online resource. |
336 ## - |
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text |
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txt |
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rdacontent |
337 ## - |
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computer |
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c |
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rdamedia |
338 ## - |
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online resource |
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cr |
-- |
rdacarrier |
347 ## - |
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text file |
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PDF |
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rda |
490 1# - SERIES STATEMENT |
Series statement |
Studies in Computational Intelligence, |
International Standard Serial Number |
1860-949X ; |
Volume number/sequential designation |
160 |
505 0# - FORMATTED CONTENTS NOTE |
Formatted contents note |
Retracted Chapter: Introduction -- Retracted Chapter: Review of Architectures Relevant to the Investigation -- Retracted Chapter: Recognition of English and Tamil Alphabets Using Kohonen’s Self-organizing Map -- Retracted Chapter: Adaptive Resonance Theory Networks -- Retracted Chapter: Applications of MicroARTMAP -- Retracted Chapter: Wavelet Transforms and MicroARTMAP -- Retracted Chapter: Gesture and Signature Recognition Using MicroARTMAP -- Retracted Chapter: Solving Scheduling Problems with Competitive Hopfield Neural Networks -- Retracted Chapter: Functional Networks -- Retracted Chapter: Conclusions and Suggestions for Future Work -- Erratum to: Pattern Recognition Using Neural and Functional Networks. |
520 ## - SUMMARY, ETC. |
Summary, etc |
The concept of pattern is universal in intelligence and discovery. The patterns in biological data contain knowledge. Discrimination of signal pattern allows personal identification by voice, hand writing, finger prints, facial images, recognition of speech, written characters and also scenes in images like identification of military targets based on radar, infrared, and video images. Possibilities are enormous in geologic, climatic, meteorologic, personality, cultural, historical, spectral, electromagnetic as well as from microscopic images of cells to macroscopic images of regions of the earth obtained from satellite scans and radio telescope images of galaxies. It is up to the researcher in some area to glean the essentials and begin to explore the classification and recognition of patterns in data that will lead to discoveries of associations and cause – effect relationships. Two outlines are suggested as the possible tracks for pattern recognition. They are neural networks and functional networks. A new approach to pattern recognition using microARTMAP and wavelet transforms in the context of hand written characters, gestures and signatures have been dealt. The Kohonen Network, Back Propagation Networks and Competitive Hopfield Neural Network have been considered for various applications. Functional networks, being a generalized form of Neural Networks where functions are learned rather than weights is compared with Multiple Regression Analysis for some applications and the results are seen to be coincident. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Engineering. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Software engineering. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Engineering mathematics. |
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Engineering. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Appl.Mathematics/Computational Methods of Engineering. |
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Software Engineering. |
700 1# - ADDED ENTRY--PERSONAL NAME |
Personal name |
Rajasekaran, Sundaramoorthy. |
Relator term |
author. |
710 2# - ADDED ENTRY--CORPORATE NAME |
Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
773 0# - HOST ITEM ENTRY |
Title |
Springer eBooks |
776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
Display text |
Printed edition: |
International Standard Book Number |
9783540851295 |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
Uniform title |
Studies in Computational Intelligence, |
-- |
1860-949X ; |
Volume number/sequential designation |
160 |
856 40 - ELECTRONIC LOCATION AND ACCESS |
Uniform Resource Identifier |
<a href="http://dx.doi.org/10.1007/978-3-540-85130-1">http://dx.doi.org/10.1007/978-3-540-85130-1</a> |
912 ## - |
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ZDB-2-ENG |