Table of Contents
Preface               32
   About On-line Help ............................................................
Options Save Page........................................................................... 73
  Examples ..................
Size command (System menu)                                                                           100

Move command (Co...
GradientSearch Family ....................................................................137
            GradientSearch F...
Hopfield Network .............................................................................183
        Principal Compon...
Filtering Example.............................................................................222
    Constructing A Linea...
Pattern Recognition Example ...........................................................265
     Introduction to Pattern Re...
Axon ........................................................................................................................
IntegratorAxon Example.......................................................................................................
setNConnections .............................................................................................................
BackSigmoidContextAxon ..........................................................405
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setBackpropOffset............................................................................................................
randomizeNetworkWeights......................................................................................................
averageOverUpdates ..........................................................................................................
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NeuroDimension Neuro Solutions HELP
NeuroDimension Neuro Solutions HELP
NeuroDimension Neuro Solutions HELP
NeuroDimension Neuro Solutions HELP
NeuroDimension Neuro Solutions HELP
NeuroDimension Neuro Solutions HELP
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NeuroDimension Neuro Solutions HELP

  1. 1. Table of Contents Preface 32 About On-line Help ................................................................................. 32 Acknowledgments .................................................................................. 32 Product Information 33 Contacting NeuroDimension.................................................................... 33 NeuroSolutions Technical Support ........................................................... 34 NeuroDimension Products and Services .................................................. 35 Level Restrictions ................................................................................... 39 Evaluation Mode..................................................................................... 40 NeuroSolutions Pricing ........................................................................... 40 NeuroSolutions University Site License Pricing ......................................... 41 Ordering Information ............................................................................... 41 Getting Started 42 System Requirements............................................................................. 42 Running the Demos ................................................................................ 42 What to do after Running the Demos ....................................................... 45 Frequently Asked Questions (FAQ) ......................................................... 45 Terms to Know....................................................................................... 50 Main Window ................................................................................... 50 Inspector.......................................................................................... 51 Breadboards .................................................................................... 52 Neural Components.......................................................................... 53 Toolbars and Palettes ....................................................................... 53 Selection and Stamping Modes ......................................................... 54 Temporary License........................................................................... 54 Menus & Toolbars .................................................................................. 55 File Menu & Toolbar Commands ....................................................... 55 Edit Menu & Toolbar Commands ....................................................... 56 Alignment Menu & Toolbar Commands .............................................. 57 Windows Menu & Toolbar Commands .............................................. 58 Component Menu ............................................................................. 59 Tools ............................................................................................... 59 Tools Menu Commands .............................................................. 59 Control Menu & Toolbar Commands ............................................ 61 Macro Menu & Toolbar Commands ............................................. 62 Customize Toolbars Page ........................................................... 63 Component Palettes......................................................................................................................................63 Command Toolbars .......................................................................................................................................64 Customize Buttons Page............................................................. 65 View ................................................................................................ 66 View Menu ................................................................................. 66 Macro Bars ................................................................................ 66 Status Bar.................................................................................. 68 Help................................................................................................. 69 Help Menu & Toolbar Commands ................................................ 69 Activate Software Panel .............................................................. 70 User Options .......................................................................................... 71 Options Window ............................................................................... 71 Options Workspace Page.................................................................. 72 1
  2. 2. Options Save Page........................................................................... 73 Examples ............................................................................................... 74 Example 1 - Toolbar Manipulation...................................................... 74 Example 2 - Component Manipulation................................................ 74 Example 3 - Inspecting a Component's Parameters ............................ 75 Simulations 76 Simulations ............................................................................................ 76 Introduction to Neural Network Simulations .............................................. 77 What Are Artificial Neural Networks ................................................... 77 A Prototype Problem......................................................................... 78 Ingredients of a Simulation ...................................................................... 79 Formulation of the problem................................................................ 79 Data Collection and Coding ............................................................... 79 Getting Data into the Network ............................................................ 80 Cross Validation ............................................................................... 81 Network Topology ............................................................................ 82 Network Training .............................................................................. 84 Probing ............................................................................................ 86 Running the Simulation ..................................................................... 86 Concepts 86 Concepts ............................................................................................... 86 NeuroSolutions Structure ........................................................................ 87 NeuroSolutions Structure .................................................................. 87 Palettes ........................................................................................... 87 Breadboard...................................................................................... 88 NeuroSolutions Graphical User Interface (GUI) ........................................ 89 NeuroSolutions Graphical User Interface (GUI) .................................. 89 Logic of the Interface........................................................................ 89 Components .................................................................................... 90 The Inspector................................................................................... 90 Single-Click vs. Double-Click............................................................. 91 File Open Dialog Box ........................................................................ 92 Save As Dialog Box .......................................................................... 92 Toolbars and Palettes ....................................................................... 92 Title Bar........................................................................................... 93 Scroll Bars ....................................................................................... 93 Network Construction ....................................................................... 94 Network Construction ................................................................. 94 Stamping ................................................................................... 94 Manipulating Components........................................................... 94 Replacing Axons and Synapses .................................................. 95 Connectors ................................................................................ 95 Cabling ...................................................................................... 96 Stacking..................................................................................... 97 Network Access ............................................................................... 97 Network Access ......................................................................... 97 Probes ....................................................................................... 98 Data Input/Output ....................................................................... 99 Transmitters and Receivers ........................................................100 Network Simulation..........................................................................100 Network Simulation....................................................................100 Application Window Commands .......................................................100 2
  3. 3. Size command (System menu) 100 Move command (Control menu) 101 Minimize command (application Control menu)............................101 Maximize command (System menu) 101 Close command (Control menus) 101 Restore command (Control menu) 102 Switch to command (application Control menu) 102 Generating Source Code .......................................................................103 Generating Source Code .................................................................103 Customized Components .......................................................................103 Customized Components .................................................................103 Testing the Network ...............................................................................104 The TestingWizard ..........................................................................104 Freezing the Network Weights..........................................................104 Cross Validation ..............................................................................104 Production Data Set.........................................................................105 Sensitivity Analysis..........................................................................105 Confusion Matrix .............................................................................105 Correlation Coefficient .....................................................................106 ROC Matrix .....................................................................................107 Performance Measures ....................................................................108 Practical Simulation Issues.....................................................................109 Practical Simulation Issues...............................................................109 Associating a File Extension with an Editor........................................110 Data Preparation .............................................................................110 Normalization File............................................................................111 Forms of Backpropagation ...............................................................112 Probing ...........................................................................................113 Saving and Fixing Network Weights..................................................113 Weights File ....................................................................................113 Saving Network Data .......................................................................118 Stop Criteria ....................................................................................118 Constructing Learning Dynamics ......................................................118 Simulating Recurrent Networks ........................................................119 Component Naming Conventions .....................................................119 Coordinating Unsupervised and Supervised Learning ........................121 Organization of NeuroSolutions ..............................................................121 Organization of NeuroSolutions ........................................................121 Activation Family .............................................................................122 Activation Family .............................................................................122 Axon Family ..............................................................................124 MemoryAxon Family ..................................................................125 FuzzyAxon Family .....................................................................127 ErrorCriteria Family .........................................................................128 Synapse Family.........................................................................130 Backprop Family..............................................................................131 Backprop Family..............................................................................131 BackAxon Family.......................................................................132 BackMemoryAxon Family...........................................................134 BackSynapse Family .................................................................136 3
  4. 4. GradientSearch Family ....................................................................137 GradientSearch Family ..............................................................137 Controls Family ...............................................................................139 Controls Family .........................................................................139 ActivationControl Family ............................................................140 BackpropControl Family.............................................................142 Unsupervised Family .......................................................................143 Unsupervised Family .................................................................143 Hebbian Family .........................................................................144 Competitive Family ....................................................................145 Kohonen Family ........................................................................146 Probe Family...................................................................................147 Probe Family.............................................................................147 Input Family ....................................................................................148 Input Family ....................................................................................148 Transmitter Family...........................................................................149 Transmitter Family...........................................................................149 Schedule Family..............................................................................150 Schedule Family..............................................................................150 Introduction to Neural Computation 151 Introduction to NeuroComputation ..........................................................151 Introduction to Neural Computation.........................................................152 Introduction to NeuroComputation ....................................................152 History of Neural Networks...............................................................152 What are Artificial Neural Networks...................................................153 Neural Network Solutions .................................................................154 Neural Network Analysis ........................................................................155 Neural Network Analysis ..................................................................155 Neural Network Taxonomies ............................................................157 Learning Paradigms.........................................................................159 Learning Paradigms...................................................................159 Cost Function ............................................................................160 Gradient Descent ......................................................................161 Constraining the Learning Dynamics.................................................166 Constraining the Learning Dynamics...........................................166 Practical Issues of Learning ...................................................................168 Practical Issues of Learning .............................................................168 Training Set ....................................................................................168 Network Size...................................................................................169 Learning Parameters .......................................................................169 Stop Criteria ....................................................................................170 Unsupervised Learning ..........................................................................171 Unsupervised learning .....................................................................171 Support Vector Machines .......................................................................174 Support Vector Machines .................................................................174 Dynamic Networks.................................................................................176 Dynamic Networks...........................................................................176 Famous Neural Topologies ....................................................................177 Famous Neural Topologies ..............................................................177 Perceptron ......................................................................................177 Multilayer Perceptron .......................................................................178 Madaline .........................................................................................180 Radial Basis Function Networks .......................................................180 Associative Memories ......................................................................181 Jordan/Elman Networks ...................................................................182 4
  5. 5. Hopfield Network .............................................................................183 Principal Component Analysis Networks ...........................................184 Kohonen Self-Organizing Maps (SOFM) ...........................................185 Adaptive Resonance Theory (ART) ..................................................187 Fukushima ......................................................................................187 Time Lagged Recurrent Networks.....................................................187 Tutorials 190 Tutorials Chapter ...................................................................................190 Running NeuroSolutions ........................................................................190 Signal Generator Example .....................................................................191 Signal Generator Example ...............................................................191 Construction Rules ..........................................................................192 Stamping Components ....................................................................193 On-line Help ....................................................................................193 Connectors .....................................................................................193 Selecting and Configuring a Component ...........................................194 Arranging Icons ...............................................................................194 Connecting Components..................................................................195 The Cursor......................................................................................195 Component Compatibility .................................................................195 Bringing in the Function Generators ..................................................196 Stacking Components......................................................................196 Accessing the Component Hierarchy ................................................197 Access Points .................................................................................198 Displaying the Output Waveform ......................................................198 Opening the Display Window............................................................199 Controlling Data Flow ......................................................................199 Configuring the Controller ................................................................199 Running the Signal Generator Example ............................................200 Things to Try with the Signal Generator ............................................201 What You have Learned from the Signal Generator Example .............202 Combination of Data Sources Example ...................................................203 Combination of Data Sources Example .............................................203 Constructing a McCulloch-Pitts Processing Element ..........................203 Preparing Files for Input into NeuroSolutions .....................................204 Things to Try with the Combination of Data Sources Example ............206 What You have Learned from the Combination of Data Sources Example207 The Perceptron and Multilayer Perceptron ..............................................207 Perceptron and Multilayer Perceptron Example .................................207 Perceptron Topology .......................................................................207 Constructing the Learning Dynamics of a Perceptron .........................208 Alternate Procedure for Constructing the Learning Dynamics of a Perceptron 210 Selecting the Learning Paradigm......................................................211 Running the Perceptron ...................................................................212 MLP Construction ............................................................................213 Running the MLP .............................................................................214 Things to Try with the Perceptron and Multilayer Perceptron Example 215 What You have Learned from the Perceptron and Multilayer Perceptron Example ......................................................................................................216 Associator Example ...............................................................................217 Associator Example .........................................................................217 Building the Associator ....................................................................217 Things to Try with the Associator ......................................................221 What you have Learned from the Associator Example .......................221 Filtering Example...................................................................................222 5
  6. 6. Filtering Example.............................................................................222 Constructing A Linear Filter..............................................................222 Things to Try with the Linear Filter....................................................224 Adaptive Network Construction.........................................................225 Running the Adaptive Network .........................................................225 Things to Try with the Adaptive Network ...........................................226 What You have Learned from the Filter Example ...............................229 Recurrent Neural Network Example ........................................................229 Recurrent Neural Network Example ..................................................229 Creating the Recurrent Topology ......................................................229 Fixed Point Learning ........................................................................231 Running the Recurrent Network ........................................................232 Things to Try with the Recurrent Network ..........................................234 What You have Learned from the Recurrent Network Example...........237 Frequency Doubler Example ..................................................................237 Frequency Doubler Example ............................................................237 Creating the Frequency Doubler Network ..........................................237 Configuration of the Trajectory..........................................................239 Running the Frequency Doubler Network ..........................................239 Using the Gamma Model to Double the Frequency ............................240 Visualizing the State Space..............................................................242 Things to Try with the Frequency Doubler Network ............................244 What You have Learned from the Frequency Doubler Example ..........246 Unsupervised Learning Example ............................................................247 Unsupervised Learning Example ......................................................247 Introduction to Unsupervised Learning ..............................................247 Noise Reduction with Oja's or Sanger's Learning ...............................248 Things to Try with the Unsupervised Network ....................................249 What You have Learned from the Unsupervised Learning Example ....251 Principle Component Analysis Example ..................................................251 Principal Component Analysis Example ............................................251 Introduction to Principal Component Analysis....................................251 Running the PCA Network ...............................................................251 Things to Try with the PCA Network..................................................253 What You have Learned from the Principal Component Analysis Example 253 Competitive Learning Example...............................................................253 Competitive Learning Example.........................................................253 Introduction to Competitive Learning .................................................253 Constructing the Competitive Network ..............................................254 Things to Try with the Competitive Network .......................................256 What You have Learned from the Competitive Learning Example.......258 Kohonen Self Organizing Feature Map (SOFM) Example .........................259 Kohonen Self Organizing Feature Map (SOFM) Example ...................259 Introduction to SOFM Example .........................................................259 SOFM Network Construction ............................................................259 Running the SOFM Network .............................................................260 Things to Try with the SOFM Network ...............................................261 What you have Learned from the Kohonen SOFM Example ...............261 Character Recognition Example .............................................................261 Character Recognition Example .......................................................261 Introduction to Character Recognition Example .................................262 Constructing the Counterpropagation Network...................................262 Running the Counterpropagation Network .........................................263 Things to Try with the Counterpropagation Network ...........................264 What You have Learned from the Character Recognition Example .....265 Pattern Recognition Example .................................................................265 6
  7. 7. Pattern Recognition Example ...........................................................265 Introduction to Pattern Recognition Example .....................................266 Constructing the Pattern Recognition Network ...................................266 Running the Pattern Recognition Network .........................................268 What you have Learned from the Pattern Recognition Example..........269 Time Series Prediction Example.............................................................269 Time Series Prediction Example.......................................................269 Introduction to Time Series Prediction Example .................................269 Constructing the TLRN Network .......................................................270 Running the TLRN Network ..............................................................271 What You have Learned from the Time Series Prediction Example .....271 Neural Network Components 271 Components .........................................................................................271 Engine Family .......................................................................................272 Activation Family ...................................................................................272 Axon Family ....................................................................................272 Axon.........................................................................................272 BiasAxon ..................................................................................273 CombinerAxon ..........................................................................274 GaussianAxon...........................................................................275 LinearAxon................................................................................276 LinearSigmoidAxon ...................................................................277 LinearTanhAxon........................................................................278 NormalizedAxon........................................................................279 NormalizedSigmoidAxon ............................................................280 SigmoidAxon.............................................................................281 SoftMaxAxon.............................................................................282 TanhAxon .................................................................................283 ThresholdAxon..........................................................................284 WinnerTakeAllAxon ...................................................................285 Access Points ...........................................................................286 Axon Family Access Points........................................................................................................................286 DLL Implementation...................................................................287 Axon DLL Implementation..........................................................................................................................287 BiasAxon DLL Implementation...................................................................................................................288 GaussianAxon DLL Implementation.........................................................................................................288 LinearAxon DLL Implementation...............................................................................................................289 LinearSigmoidAxon DLL Implementation.................................................................................................290 LinearTanhAxon DLL Implementation......................................................................................................291 SigmoidAxon DLL Implementation............................................................................................................292 SoftMaxAxon DLL Implementation............................................................................................................292 TanhAxon DLL Implementation.................................................................................................................293 ThresholdAxon DLL Implementation........................................................................................................294 WinnerTakeAllAxon DLL Implementation ................................................................................................295 Examples ..................................................................................296 Axon Example...............................................................................................................................................296 BiasAxon Example.......................................................................................................................................297 GaussianAxon Example..............................................................................................................................298 LinearAxon Example...................................................................................................................................299 LinearSigmoidAxon Example.....................................................................................................................300 LinearTanhAxon Example..........................................................................................................................301 SigmoidAxon Example................................................................................................................................302 SoftMaxAxon Example................................................................................................................................303 TanhAxon Example.....................................................................................................................................304 ThresholdAxon Example.............................................................................................................................305 WinnerTakeAllAxon Example.....................................................................................................................306 Macro Actions ...........................................................................307 7
  8. 8. Axon ...............................................................................................................................................................307 Axon Macro Actions.....................................................................................................................................307 setRows .........................................................................................................................................................308 cols .................................................................................................................................................................308 fireNext...........................................................................................................................................................308 fireNextOnReset...........................................................................................................................................309 rows ................................................................................................................................................................309 setCols ...........................................................................................................................................................309 setDimensions ..............................................................................................................................................309 setFireNext ....................................................................................................................................................310 setFireNextOnReset....................................................................................................................................310 Gaussian Axon .............................................................................................................................................311 GaussianAxon Macro Actions....................................................................................................................311 assignCenters...............................................................................................................................................311 assignVariance.............................................................................................................................................311 neighbors.......................................................................................................................................................311 setEngineData..............................................................................................................................................312 setNeighbors.................................................................................................................................................312 Linear Axon...................................................................................................................................................312 LinearAxon Macro Actions..........................................................................................................................312 beta.................................................................................................................................................................313 setBeta...........................................................................................................................................................313 setWeightMean.............................................................................................................................................313 setWeightVariance.......................................................................................................................................314 weightMean...................................................................................................................................................314 weightVariance.............................................................................................................................................314 Winner Take All Axon..................................................................................................................................314 WinnerTakeAllAxon Macro Actions...........................................................................................................314 maxWinner....................................................................................................................................................315 setMaxWinner...............................................................................................................................................315 Inspectors .......................................................................................315 Axon Inspector ..........................................................................315 GaussianAxon Inspector ............................................................316 WinnerTakeAllAxon Inspector ....................................................318 Engine Inspector .............................................................................319 Soma Family Inspector...............................................................................................................................321 Transfer Function Inspector........................................................322 Drag and Drop.................................................................................323 Axon Family Drag and Drop .......................................................323 MemoryAxon Family ........................................................................323 ContextAxon .............................................................................323 GammaAxon.............................................................................324 IntegratorAxon ..........................................................................325 LaguarreAxon ...........................................................................326 SigmoidContextAxon .................................................................327 SigmoidIntegratorAxon ..............................................................328 TanhContextAxon......................................................................329 TanhIntegratorAxon ...................................................................330 TDNNAxon................................................................................331 DLL Implementation...................................................................332 ContextAxon DLL Implementation............................................................................................................332 GammaAxon DLL Implementation............................................................................................................332 IntegratorAxon DLL Implementation.........................................................................................................333 LaguarreAxon DLL Implementation ..........................................................................................................334 SigmoidContextAxon DLL Implementation..............................................................................................335 SigmoidIntegratorAxon DLL Implementation...........................................................................................336 TanhContextAxon DLL Implementation...................................................................................................337 TanhIntegratorAxon DLL Implementation................................................................................................338 TDNNAxon DLL Implementation ...............................................................................................................338 Examples ..................................................................................339 8
  9. 9. IntegratorAxon Example.............................................................................................................................339 TanhIntegratorAxon Example....................................................................................................................340 SigmoidIntegratorAxon Example...............................................................................................................341 ContextAxon Example.................................................................................................................................343 SigmoidContextAxon Example..................................................................................................................344 TanhContextAxon Example........................................................................................................................345 GammaAxon Example................................................................................................................................346 LaguarreAxon Example...............................................................................................................................347 TDNNAxon Example...................................................................................................................................348 Inspectors .................................................................................349 TDNNAxon Inspector...................................................................................................................................349 Feedback Inspector.....................................................................................................................................350 Macro Actions ...........................................................................351 TDNN Axon...................................................................................................................................................351 TDNNAxon Macro Actions..........................................................................................................................351 setTapDelay..................................................................................................................................................352 setTaps ..........................................................................................................................................................352 tapDelay.........................................................................................................................................................352 taps.................................................................................................................................................................352 FuzzyAxon Family ...........................................................................353 BellFuzzyAxon ..........................................................................353 GaussianFuzzyAxon..................................................................354 DLL Implementation...................................................................354 GaussianFuzzyAxon DLL Implementation...............................................................................................354 BellFuzzyAxon DLL Implementation.........................................................................................................356 Inspectors .................................................................................357 FuzzyAxon Inspector...................................................................................................................................357 Synapse Family...............................................................................357 ArbitrarySynapse.......................................................................357 CombinerSynapse.....................................................................358 ContractorSynapse....................................................................359 ExpanderSynapse .....................................................................360 ModularSynapse .......................................................................361 FullSynapse ..............................................................................362 SVMOutputSynapse ..................................................................363 Synapse ...................................................................................363 Access Points ...........................................................................364 Synapse Family Access Points..................................................................................................................364 DLL Implementation...................................................................365 FullSynapse DLL Implementation.............................................................................................................365 Synapse DLL Implementation....................................................................................................................366 Drag and Drop...........................................................................367 Synapse Family Drag and Drop.................................................................................................................367 Inspectors .................................................................................367 ArbitrarySynapse Inspector........................................................................................................................367 CombinerSynapse Inspector......................................................................................................................369 ContractorSynapse Inspector.....................................................................................................................370 ExpanderSynapse Inspector......................................................................................................................371 ModularSynapse Inspector.........................................................................................................................371 Synapse Inspector.......................................................................................................................................372 Macro Actions ...........................................................................373 ArbitrarySynapse..........................................................................................................................................373 ArbitrarySynapse