实例介绍
【实例简介】Java 神经网络介绍
【实例截图】
【核心代码】
【实例截图】
【核心代码】
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
标签： java Neural Network
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