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|a (OCoLC)ebqac1347023270
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|a ebqac7104479
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|d OCLCQ
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|a 9781119214359
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|a 1119214351
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|a (OCoLC)1347023270
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|a GWRE
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| 100 |
1 |
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|a Keller, James M.
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| 245 |
1 |
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|a Fundamentals of Computational Intelligence
|b Neural Networks, Fuzzy Systems, and Evolutionary Computation.
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| 260 |
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|a Newark :
|b John Wiley & Sons, Incorporated,
|c 2016.
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| 300 |
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|a 1 online resource (381 p.).
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| 336 |
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|a text
|b txt
|2 rdacontent
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| 337 |
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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| 490 |
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|a New York Academy of Sciences Ser.
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| 500 |
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|a Description based upon print version of record.
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0 |
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|a Fundamentals of Computational Intelligence: Neural Networks, Fuzzy Systems, and Evolutionary Computation -- Table of Contents -- Acknowledgments -- Chapter 1: Introduction to Computational Intelligence -- 1.1 Welcome to Computational Intelligence -- 1.2 What Makes This Book Special -- 1.3 What This Book Covers -- 1.4 How to Use This Book -- 1.5 Final Thoughts Before You Get Started -- Part I: Neural Networks -- Chapter 2: Introduction and Single-Layer Neural Networks -- 2.1 Short History of Neural Networks -- 2.2 Rosenblatt's Neuron -- 2.3 Perceptron Training Algorithm -- 2.3.1 Test Problem
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| 505 |
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|a 2.3.2 Constructing Learning Rules -- 2.3.3 Unified Learning Rule -- 2.3.4 Training Multiple-Neuron Perceptrons -- 2.3.4.1 Problem Statement -- 2.4 The Perceptron Convergence Theorem -- 2.5 Computer Experiment Using Perceptrons -- 2.6 Activation Functions -- 2.6.1 Threshold Function -- 2.6.2 Sigmoid Function -- Exercises -- Chapter 3: Multilayer Neural Networks and Backpropagation -- 3.1 Universal Approximation Theory -- 3.2 The Backpropagation Training Algorithm -- 3.2.1 The Description of the Algorithm -- 3.2.2 The Strategy for Improving the Algorithm
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| 505 |
8 |
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|a 3.2.3 The Design Procedure of the Algorithm -- 3.3 Batch Learning and Online Learning -- 3.3.1 Batch Learning -- 3.3.2 Online Learning -- 3.4 Cross-Validation and Generalization -- 3.4.1 Cross-Validation -- 3.4.2 Generalization -- 3.4.3 Convolutional Neural Networks -- 3.5 Computer Experiment Using Backpropagation -- Exercises -- Chapter 4: Radial-Basis Function Networks -- 4.1 Radial-Basis Functions -- 4.2 The Interpolation Problem -- 4.3 Training Algorithms for Radial-Basis Function Networks -- 4.3.1 Layered Structure of a Radial-Basis Function Network
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| 505 |
8 |
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|a 4.3.2 Modification of the Structure of RBF Network -- 4.3.3 Hybrid Learning Process -- 4.4 Universal Approximation -- 4.5 Kernel Regression -- Exercises -- Chapter 5: Recurrent Neural Networks -- 5.1 The Hopfield Network -- 5.2 The Grossberg Network -- 5.2.1 Basic Nonlinear Model -- 5.2.2 Two-Layer Competitive Network -- 5.2.2.1 Layer 1 -- 5.2.2.2 Layer 2 -- 5.2.2.3 Learning Law -- Basic Nonlinear Model: Leaky Integrator -- Layer 1 -- Layer 2 -- 5.3 Cellular Neural Networks -- 5.4 Neurodynamics and Optimization -- 5.5 Stability Analysis of Recurrent Neural Networks
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| 505 |
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|a 5.5.1 Stability Analysis of the Hopfield Network -- 5.5.2 Stability Analysis of the Cohen-Grossberg Network -- Exercises -- Part II: Fuzzy Set Theory and Fuzzy Logic -- Chapter 6: Basic Fuzzy Set Theory -- 6.1 Introduction -- 6.2 A Brief History -- 6.3 Fuzzy Membership Functions and Operators -- 6.3.1 Membership Functions -- 6.3.2 Basic Fuzzy Set Operators -- 6.4 Alpha-Cuts, the Decomposition Theorem, and the Extension Principle -- 6.5 Compensatory Operators -- 6.6 Conclusions -- Exercises -- Chapter 7: Fuzzy Relations and Fuzzy Logic Inference -- 7.1 Introduction
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| 500 |
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|a 7.2 Fuzzy Relations and Propositions
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| 776 |
0 |
8 |
|i Print version:
|a Keller, James M.
|t Fundamentals of Computational Intelligence
|d Newark : John Wiley & Sons, Incorporated,c2016
|z 9781119214403
|
| 830 |
|
0 |
|a New York Academy of Sciences Ser.
|
| 856 |
4 |
0 |
|u https://ebookcentral.proquest.com/lib/ucb/detail.action?docID=7104479
|z Full Text (via ProQuest)
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| 915 |
|
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|a M
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| 956 |
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|a Ebook Central Academic Complete
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| 956 |
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|b Ebook Central Academic Complete
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| 998 |
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|b Added to collection pqebk.acadcomplete
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| 994 |
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|a 92
|b COD
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| 952 |
f |
f |
|p Can circulate
|a University of Colorado Boulder
|b Online
|c Online
|d Online
|h Library of Congress classification
|i web
|
