MARC details
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01811nam a22002057a 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
CUTN |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20180920124120.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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180920b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9788120312531 |
| 041 ## - LANGUAGE CODE |
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| Language |
English |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.32 |
| Item number |
YEN |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Yegnanarayana, B. |
| 245 ## - TITLE STATEMENT |
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| Title |
Artificial neural networks |
| Statement of responsibility, etc |
B. Yegnanarayana |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Place of publication, distribution, etc |
New Delhi : |
| Name of publisher, distributor, etc |
PHI Learning, |
| Date of publication, distribution, etc |
2015. |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
xiii, 461 p.: |
| Dimensions |
22 cm. |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Title |
Basics of Artificial Neural Networks |
| -- |
Activation and Synaptic Dynamics |
| -- |
Functional Units of ANN for Pattern Recognition Tasks |
| -- |
Feedforward Neural Networks |
| -- |
Feedback Neural Networks |
| -- |
Competitive Learning Neural Networks |
| -- |
Architectures for Complex Pattern Recognition Tasks |
| -- |
Applications of ANN |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Neural networks (Computer science) |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
General Books |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
Designed as an introductory level textbook on Artificial Neural Networks at the postgraduate and senior undergraduate levels in any branch of engineering, this self-contained and well-organized book highlights the need for new models of computing based on the fundamental principles of neural networks.<br/><br/>Professor Yegnanarayana compresses, into the covers of a single volume, his several years of rich experience, in teaching and research in the areas of speech processing, image processing, artificial intelligence and neural networks. He gives a masterly analysis of such topics as Basics of artificial neural networks, Functional units of artificial neural networks for pattern recognition tasks, Feedforward and Feedback neural networks, and Archi-tectures for complex pattern recognition tasks. Throughout, the emphasis is on the pattern processing feature of the neural networks. Besides, the presentation of real-world applications provides a practical thrust to the discussion. |
