基本信息

---

下载

   友情提示：（无需注册或充值，赞助后即可获取资源下载链接）

---

     嘿，亲！知识可是无价之宝呢，但咱这精心整理的资料也耗费了不少心血呀。小小地破费一下，绝对物超所值哦！如有下载和支付问题，请联系我们QQ(微信同号)：813200300

本次赞助数额为： 1 元　

支付宝支付

微信支付

   源码介绍

---

Java 神经网络介绍

Contents at a Glance
Introduction ......................................................................................................XXXV
Chapter 1: Overview of Neural Networks.........................................................39
Chapter 2: Matrix Operations ...........................................................................61
Chapter 3: Using a Hopfield Neural Network ...................................................83
Chapter 4: How a Machine Learns ...................................................................119
Chapter 5: Feedforward Neural Networks .......................................................143
Chapter 6: Understanding Genetic Algorithms ................................................173
Chapter 7: Understanding Simulated Annealing .............................................199
Chapter 8: Pruning Neural Networks ...............................................................213
Chapter 9: Predictive Neural Networks............................................................233
Chapter 10: Application to the Financial Markets ...........................................247
Chapter 11: Understanding the Self-Organizing Map .....................................277
Chapter 12: OCR with the Self-Organizing Map...............................................311
Chapter 13: Bot Programming and Neural Networks......................................333
Chapter 14: The Future of Neural Networks ....................................................385
Appendix A: Downloading Examples ..............................................................395
Appendix B: Mathematical Background .........................................................399
Appendix C: Common Threshold Functions....................................................403
Appendix D: Executing Examples....................................................................409
Glossary ............................................................................................................417
XIV Introduction to Neural Networks with Java, Second Edition
XV
Contents
Introduction ......................................................................................................XXXV
A Historical Perspective on Neural Networks ...........................................XXXVI
Chapter 1: Overview of Neural Networks.........................................................39
Solving Problems with Neural Networks...................................................43
Problems Commonly Solved With Neural Networks .................................46
Using a Simple Neural Network.................................................................49
Chapter Summary ......................................................................................55
Vocabulary..................................................................................................56
Questions for Review .................................................................................58
Chapter 2: Matrix Operations ...........................................................................61
The Weight Matrix ......................................................................................61
Matrix Classes............................................................................................63
Constructing a Matrix ................................................................................68
Matrix Operations.......................................................................................70
Bipolar Operations......................................................................................78
Chapter Summary ......................................................................................79
Vocabulary..................................................................................................79
Questions for Review .................................................................................80
Chapter 3: Using a Hopfield Neural Network ...................................................83
The Hopfield Neural Network.....................................................................83
Recalling Patterns ......................................................................................85
Creating a Java Hopfield Neural Network .................................................90
Simple Hopfield Example ...........................................................................96
Visualizing the Weight Matrix ...................................................................100
Hopfield Pattern Recognition Applet .........................................................107
Chapter Summary ......................................................................................115
Vocabulary..................................................................................................116
Questions for Review .................................................................................116
Chapter 4: How a Machine Learns ...................................................................119
Learning Methods.......................................................................................119
Error Calculation.........................................................................................123
Training Algorithms....................................................................................128
Chapter Summary ......................................................................................140
Vocabulary..................................................................................................140
Questions for Review .................................................................................141
Chapter 5: Feedforward Neural Networks .......................................................143
Contents
XVI Introduction to Neural Networks with Java, Second Edition
A Feedforward Neural Network .................................................................144
Solving the XOR Problem ...........................................................................146
Activation Functions ..................................................................................150
The Number of Hidden Layers....................................................................157
Examining the Feedforward Process.........................................................159
Examining the Backpropagation Process .................................................162
Chapter Summary ......................................................................................169
Vocabulary..................................................................................................169
Questions for Review .................................................................................170
Chapter 6: Understanding Genetic Algorithms ................................................173
Genetic Algorithms.....................................................................................173
Understanding Genetic Algorithms............................................................175
How Genetic Algorithms Work ...................................................................176
Implementation of a Generic Genetic Algorithm.......................................178
The Traveling Salesman Problem ..............................................................182
Implementing the Traveling Salesman Problem .......................................183
XOR Operator..............................................................................................186
Tic-Tac-Toe .................................................................................................189
Chapter Summary ......................................................................................195
Vocabulary..................................................................................................196
Questions for Review .................................................................................197
Chapter 7: Understanding Simulated Annealing .............................................199
Simulated Annealing Background .............................................................199
Understanding Simulated Annealing.........................................................200
Simulated Annealing and the Traveling Salesman Problem.....................203
Implementing Simulated Annealing ..........................................................204
Simulated Annealing for the Traveling Salesman Problem.......................206
Simulated Annealing for Neural Networks................................................207
Chapter Summary ......................................................................................209
Vocabulary..................................................................................................210
Questions for Review .................................................................................210
Chapter 8: Pruning Neural Networks ...............................................................213
Understanding Pruning .............................................................................213
Pruning Algorithms ...................................................................................215
Implementing Pruning................................................................................218
Chapter Summary ......................................................................................229
Vocabulary..................................................................................................230
Questions for Review .................................................................................230
XVII
Chapter 9: Predictive Neural Networks............................................................233
How to Predict with a Neural Network......................................................233
Predicting the Sine Wave ...........................................................................235
Chapter Summary ......................................................................................243
Vocabulary..................................................................................................244
Questions for Review .................................................................................244
Chapter 10: Application to the Financial Markets ...........................................247
Collecting Data for the S&P 500 Neural Network......................................247
Running the S&P 500 Prediction Program.................................................251
Creating the Actual S&P 500 Data .............................................................253
Training the S&P 500 Network...................................................................262
Attempting to Predict the S&P 500 ...........................................................272
Chapter Summary ......................................................................................274
Vocabulary..................................................................................................274
Questions for Review .................................................................................275
Chapter 11: Understanding the Self-Organizing Map .....................................277
Introducing the Self-Organizing Map ........................................................277
Implementing the Self-Organizing Map ....................................................286
The SOM Implementation Class.................................................................289
The SOM Training Class .............................................................................290
Using the Self-organizing Map ..................................................................297
Chapter Summary ......................................................................................307
Vocabulary..................................................................................................308
Questions for Review .................................................................................308
Chapter 12: OCR with the Self-Organizing Map...............................................311
The OCR Application...................................................................................311
Implementing the OCR Program................................................................314
Downsampling the Image ..........................................................................319
Using the Self-Organizing Map..................................................................325
Beyond This Example .................................................................................329
Chapter Summary ......................................................................................330
Vocabulary..................................................................................................330
Questions for Review .................................................................................330
Chapter 13: Bot Programming and Neural Networks......................................333
A Simple Bot...............................................................................................333
Introducing the Neural Bot.........................................................................339
Gathering Training Data for the Neural Bot...............................................341
Training the Neural Bot ..............................................................................356
XVIII Introduction to Neural Networks with Java, Second Edition
Querying the Neural Bot.............................................................................374
Chapter Summary ......................................................................................381
Vocabulary..................................................................................................381
Questions for Review .................................................................................381
Chapter 14: The Future of Neural Networks ....................................................385
Neural Networks Today ..............................................................................385
A Fixed Wing Neural Network ....................................................................386
Quantum Computing ..................................................................................388
Reusable Neural Network Frameworks.....................................................391
Chapter Summary ......................................................................................392
Vocabulary..................................................................................................393
Appendix A: Downloading Examples ..............................................................395
Appendix B: Mathematical Background .........................................................399
Matrix Operations.......................................................................................399
Sigma Notation...........................................................................................399
Derivatives and Integrals ...........................................................................400
Appendix C: Common Threshold Functions....................................................403
Linear Threshold Function .........................................................................403
Sigmoidal Threshold Function ...................................................................404
Hyperbolic Tangent Threshold Function ....................................................405
Appendix D: Executing Examples....................................................................409
Command Line............................................................................................409
Eclipse IDE ..................................................................................................410
Classes to Execute .....................................................................................413
Glossary ............................................................................................................417