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No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the publisher.  \nThis book was printed and bound in the United States of America.  \nLibrary of Congress Cataloging-in-Publication Data  \nWeitzenfeld, Alfredo.  \nThe neural simulation language : a system for brain modeling / Alfredo Weitzenfeld, Michael Arbib, Amanda Alexander.  \n[p. cm](p. cm).  \nIncludes bibliographical references and index.  \nISBN 0-262-73149-5 (pbk. : alk. Paper)  \n1. Neural networks (Neurobiology) 2. Neural networks (Computer science)  \n3. Brain—Computr simulation. I. Arbib, Michael A. II. Alexander, Amanda. III. Title. QP363 .3 . W45 2002  \n006.3'2–dc21  \n2001056253  \nPreface xiii  \nAcknowledgments xvii  \n1 Introduction 1  \n1.1 Neural Networks 1  \nModeling  \nSimulation  \n1.2 Modularity, Object-Oriented Programming, and Concurrency 2  \nModularity in Neural Networks 2  \nObject-Oriented Programming 4  \nConcurrency in Neural Networks 4  \n1.3 Modeling and Simulation in NSL 5  \nModeling 5  \nModules 5  \nNeural Networks 6  \nSimulation 7  \n1.4 The NSL System 9  \nSimulation System 10  \nSchematic Capture System 11  \nModel/Module Libraries 11  \nBasic Hierarchy 12  \n1.5 Summary 13  \n2 Simulation in NSL 15  \n2.1 Selecting a Model 15  \n2.2 Simulation Interface 17  \n2.3 Simulating a Model 18  \n2.4 Maximum Selector 19  \nModel Description 19  \nSimulation Interaction 20  \n2.5 Hopfield 24  \nModel Description 25  \nSimulation Interaction 26  \n2.6 Backpropagation 31  \nModel Description 32  \nSimulation Interaction 35  \n2.7 Summary 38  \n3 Modeling in NSL 39  \n3.1 Implementing Model Architectures with NSLM 39  \nModules and Models 39  \nNeural Networks 46  \n3.2 Visualizing Model Architectures with SCS 50  \n3.3 Maximum Selector 52  \nModel Implementation 53  \n3.4 Hopfield 56  \nModel Implementation 56  \n3.5 Backpropagation 60  \nModel Implementation 60  \n3.6 Summary 68  \n4 Schematic Capture System 69  \n4.1 SCS Tools 69  \nSchematic Editor (SE) 69  \nIcon Editor (IE) 69  \nNSLM Editor (NE) 70  \nLibrary Path Editor (LPE) 70  \nLibrary Manager (LM) 70  \nConsistency Checker (CC) 70  \nNSLM Generator (NG) 70  \nNSLM Viewer (NV) 70  \n4.2 An Example Using SCS 70  \nCreate a Library 70  \nCreate Icons 71  \nSpecifying the Ports on the Icon 74  \nCreating the Schematic 77  \nMouse Action Commands 84  \nAutomatic Generation of Code 84  \nManual Generation of Leaf Level Code 85  \nGenerating NSLM Code 87  \nCompiling and Generating the Executable File 88  \nReusing Modules and Models 88  \nCopying Existing Modules and Models 88  \n4.3 Summary 88  \n5 User Interface and Graphical Windows 89  \n5.1 NSL Executive User Interface 89  \nSystem Menu 89  \nEdit Menu 89  \nProtocol Menu 90  \nSimulation Menu 90  \nTrain Menu 90  \nRun Menu 91  \nDisplay Menu 92  \nHelp menu 92  \n5.2 NslOutFrames 92  \nThe NslOutFrame’s Frame Menu 93  \nThe NslOutFrame’s Canvas Menu 96  \nNSL Output Graph Types 98  \n5.3 NslInFrames 100  \nThe NslInFrame’s Menu 100  \nThe NslInFrame’s Canvas Menu 101  \nNSL Input Graph Types 101  \n5.4 Summary 102  \n6 The Modeling Language NSLM 103  \n6.1 Overview 103  \nGeneral Conventions 103  \nTypes 104  \nVariables, Attributes, and Methods 104  \nAttribute Reference Hierarchies 105  \nClass Reference Hierarchies 106  \nPredefined Reference Variables 106  \nImporting Libraries 106  \nVerbatim 107  \n6.2 Primitive Types 107  \nDefined Types 107  \nDeclarations 108  \nExpressions 109  \nControl Statements 110  \nConversions, Casting, and Promotions 111  \n6.3 Object Types 112  \nDefined Types 112  \nDeclarations and Instantiations 114  \nExpressions 117  \nControl Statements 121  \nConversions, C","cbCaivGUaorLRyJz","https://ap.wps.com/l/cbCaivGUaorLRyJz","pdf",4216163,460,"English","# Preface\n# Acknowledgments\n# 1 Introduction\n## 1.1 Neural Networks\n## 1.2 Modularity, Object-Oriented Programming, and Concurrency\n## 1.3 Modeling and Simulation in NSL\n## 1.4 The NSL System\n## 1.5 Summary\n# 2 Simulation in NSL\n## 2.1 Selecting a Model\n## 2.2 Simulation Interface\n## 2.3 Simulating a Model\n## 2.5 Hopfield\n## 2.6 Backpropagation\n## 2.7 Summary\n# 3 Modeling in NSL\n## 3.1 Implementing Model Architectures with NSLM\n## 3.2 Visualizing Model Architectures with SCS\n## 3.4 Hopfield\n## 3.5 Backpropagation\n## 3.6 Summary\n# 4 Schematic Capture System\n## 4.1 SCS Tools\n## 4.2 An Example Using SCS\n## 4.3 Summary\n# 5 User Interface and Graphical Windows\n## 5.1 NSL Executive User Interface\n## 5.2 NslOutFrames\n## 5.3 NslInFrames\n## 5.4 Summary\n# 6 The Modeling Language NSLM\n## 6.1 Overview\n## 6.2 Primitive Types\n## 6.4 Creation of New Object Types\n## 6.5 Creation of New Module Types\n## 6.6 Creation of New Model Types\n## 6.7 Summary\n# 7 The Scripting Language NSLS\n## 7.1 Overview\n## 7.2 TCL Primitives Types\n## 7.3 NSL Objects, Modules, and Model Types\n## 7.4 Input Output\n## 7.6 Summary\n# 8 Adaptive Resonance Theory\n## 8.1 Introduction\n## 8.2 Model Description\n## 8.3 Model Implementation\n## 8.4 Simulation and Results\n## 8.5 Summary\n# 9 Depth Perception\n## 9.1 Introduction\n## 9.2 Model Description: Disparity\n## 9.4 Simulation and Results: Disparity\n## 9.6 Model Implementation: Disparity and Accommodation\n## 9.8 Summary\n# 10 Retina\n## 10.1 Introduction\n## 10.2 Model Description","[{\"question\":\"What is NSL and what is it used for?\",\"answer\":\"NSL is a system for brain modeling based on neural simulation. It supports modeling neural network structures and running simulations to study behaviors and results.\"},{\"question\":\"How does the book approach simulation in NSL?\",\"answer\":\"Simulation in NSL is explained through selecting a model, using a simulation interface, and simulating the model. It also covers specific simulation interactions for Hopfield networks and backpropagation.\"},{\"question\":\"What roles do NSLM and NSLS play?\",\"answer\":\"NSLM is the modeling language that defines types, variables, expressions, control flow, and mechanisms for creating new object, module, and model types. NSLS is the scripting language that provides supporting scripting primitives, handles input/output, and drives simulation objects and parameters.\"}]","The Neural Simulation Language - A System for Brain Modeling | PDF",1789975133,1159]