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Pattern recognition using neural networks : theory and algorithms for engineers and scientists / Carl G. Looney.

By: Looney, Carl G.
Publisher: New York : Oxford University Press, 1997Description: xix, 458 p. : ill. ; 25 cm.ISBN: 0195079205 (cloth).Subject(s): Pattern recognition systems | Neural networks (Computer science)DDC classification: 006.4
Contents:
Part I: Fundamentals of pattern recognition -- 0. Basic concepts of pattern recognition - 1. Decision - theoretic algorithms - 2. Structural pattern recognition -- Part II: Introductory neural networks - 3. Artificial neural network structures - 4. Supervised training via error backpropagation: derivations -- Part III: Advanced fundamentals of neural networks - 5. Acceleration and stabilization of supervised gradient training of MLPs - 6. Supervised training via strategic search - 7. Advances in network algorithms for classification and recognition - 8. Recurrent neural networks -- Part IV: Neural, feature, and data engineering: 9. Neural engineering and testing of FANNs - 10. Feature and data engineering -- Part V: Testing and applications: 11. Some comparative studies of feedforward artificial neural networks - 12. Pattern recognition applications.
Item type Current location Call number Copy number Status Notes Date due Barcode Remark
Main Collection TU External Storage-LCS
006.4 LOO (Browse shelf) 1 Available SOCIT, 547233 1001004713 Please fill up online form at https://taylorslibrary.taylors.edu.my/services/external_storage1

Includes bibliographical references and index.

Part I: Fundamentals of pattern recognition -- 0. Basic concepts of pattern recognition - 1. Decision - theoretic algorithms - 2. Structural pattern recognition -- Part II: Introductory neural networks - 3. Artificial neural network structures - 4. Supervised training via error backpropagation: derivations -- Part III: Advanced fundamentals of neural networks - 5. Acceleration and stabilization of supervised gradient training of MLPs - 6. Supervised training via strategic search - 7. Advances in network algorithms for classification and recognition - 8. Recurrent neural networks -- Part IV: Neural, feature, and data engineering: 9. Neural engineering and testing of FANNs - 10. Feature and data engineering -- Part V: Testing and applications: 11. Some comparative studies of feedforward artificial neural networks - 12. Pattern recognition applications.