Neural networks: algorithms, applications and programming techniques / James A. Freeman and David m. Skapura

By: Freeman, James AMaterial type: TextTextPublication details: Uttar Pradesh : Pearson , c1991Description: 415 p. illISBN: 9788131708088 (pb)DDC classification: 006.3
Contents:
Chapter 1 Introduction to ANS Technology 1.1 Elementary Neurophysiology's 22 1.2 From Neurons to ANS 31 1.3 ANS Simulation 44 Bibliography 55 Chapter 2 Adaline and Madaline 59 2.1 Review of Signal Processing 59 2.2 Adaline and the Adaptive Linear Combiner 69 2.3 Applications of Adaptive Signal Processing 82 2.4 The Madaline 86 2.5 Simulating the Adaline 93 Bibliography 100 Chapter 3 Backpropagatlon 103 3.1 The Backpropagation Network 103 3.2 The Generalized Delta Rule 107 3.3 Practical Considerations 117 3.4 BPN Applications 120 3.5 The Backpropagation Simulator 128 Bibliography 138 Chapter 4 4.1 Associative-Memory Definitions 142 i S teXiq 4.2 The BAM 145 > Uim 4.3 The Hopfield Memory 155 4.4 Simulating the BAM 170 Bibliography 181 Chapter 5 Simulated Annealing 183 5.1 Information Theory and Statistical Mechanics 185 5.2 The Boltzmann Machine 193 5.3 The Boltzmann Simulator 203 5.4 Using the Boltzmann Simulator 221 Bibliography 226 ^^ Chapter 6 The Counterpropagation Network 227 6.1 CRN Building Blocks 229 6.2 CRN Data Rrocessmg 249 6.3 An Image-Classification Example 258 6.4 The CRN Simulator 261 Bibliography 276 Chapter 7 Self-Organizing Maps 277 7.1 SOM Data Rrocessing 279 7.2 Applications of Self-Organizing Maps 288 7.3 Simulating the SOM 293 Bibliography 303 Chapter 8 Adaptive Resonance Theory 305 8.1 ART Network Description 307 8.2 ART1 312 8.3 ART2 330 A 8.4 The ART1 Simulator 341 . 8.5 ART2 Simulation 350 Bibliography 352 Chapter 9 Spatiotemporal Pattern Classification 355 9.1 The Formal Avalanche 356 9.2 Architectures of Spatiotemporal Networks (STNS) 359 9.3 The Sequential Competitive Avalanche Field 369 9.4 Applications of STNS 377 9.5 STN Simulation 378 Bibliography 385 Chapter TO The Neocognitron 387 10.1 Neocognitron Architecture 390 10.2 Neocognitron Data Processing 395 10.3 Performance of the Neocognitron 403 10.4 Addition of Lateral Inhibition and Feedback to the Neocognitron 404 Bibliography 407
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
General Books General Books Central Library, Sikkim University
General Book Section
006.3 FRE/N (Browse shelf(Opens below)) Available P35909
Total holds: 0

Chapter 1
Introduction to ANS Technology
1.1 Elementary Neurophysiology's 22
1.2 From Neurons to ANS 31
1.3 ANS Simulation 44
Bibliography 55
Chapter 2
Adaline and Madaline 59
2.1 Review of Signal Processing 59

2.2 Adaline and the Adaptive Linear Combiner 69
2.3 Applications of Adaptive Signal Processing 82
2.4 The Madaline 86
2.5 Simulating the Adaline 93
Bibliography 100
Chapter 3
Backpropagatlon 103
3.1 The Backpropagation Network 103
3.2 The Generalized Delta Rule 107
3.3 Practical Considerations 117
3.4 BPN Applications 120
3.5 The Backpropagation Simulator 128
Bibliography 138
Chapter 4

4.1 Associative-Memory Definitions 142 i S teXiq
4.2 The BAM 145 > Uim

4.3 The Hopfield Memory 155
4.4 Simulating the BAM 170
Bibliography 181
Chapter 5
Simulated Annealing 183
5.1 Information Theory and Statistical Mechanics 185
5.2 The Boltzmann Machine 193
5.3 The Boltzmann Simulator 203
5.4 Using the Boltzmann Simulator 221
Bibliography 226 ^^
Chapter 6
The Counterpropagation Network 227
6.1 CRN Building Blocks 229
6.2 CRN Data Rrocessmg 249
6.3 An Image-Classification Example 258
6.4 The CRN Simulator 261
Bibliography 276
Chapter 7
Self-Organizing Maps 277
7.1 SOM Data Rrocessing 279
7.2 Applications of Self-Organizing Maps 288
7.3 Simulating the SOM 293
Bibliography 303
Chapter 8
Adaptive Resonance Theory 305
8.1 ART Network Description 307
8.2 ART1 312
8.3 ART2 330 A
8.4 The ART1 Simulator 341 .
8.5 ART2 Simulation 350
Bibliography 352
Chapter 9
Spatiotemporal Pattern Classification 355
9.1 The Formal Avalanche 356
9.2 Architectures of Spatiotemporal Networks (STNS) 359

9.3 The Sequential Competitive Avalanche Field 369
9.4 Applications of STNS 377
9.5 STN Simulation 378
Bibliography 385
Chapter TO
The Neocognitron 387
10.1 Neocognitron Architecture 390
10.2 Neocognitron Data Processing 395
10.3 Performance of the Neocognitron 403
10.4 Addition of Lateral Inhibition and Feedback to the
Neocognitron 404
Bibliography 407

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