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Cellular neural networks : analysis, design, and optimization

Author: Martin Hänggi; George S Moschytz
Publisher: Boston : Kluwer Academic Publishers, ©2000.
Edition/Format:   Print book : EnglishView all editions and formats
Summary:

Cellular Neural Networks (CNNs) constitute a class of nonlinear, recurrent and locally coupled arrays of identical dynamical cells that operate in parallel.

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Material Type: Internet resource
Document Type: Book, Internet Resource
All Authors / Contributors: Martin Hänggi; George S Moschytz
ISBN: 0792378911 9780792378914
OCLC Number: 44650952
Description: x, 148 pages : illustrations ; 24 cm
Contents: 1.1 Motivation 1 --
1.2 CNN Basics 2 --
1.3 Planar and Bipolar CNNs 5 --
1.4 Circuit Implementation of CNNs 8 --
1.5 Outline of the Book 9 --
2 Locally Regular CNNs 11 --
2.2 Definition of Local Regularity 11 --
2.3 How to Check for Local Regularity? 15 --
3 Robust Template Design 23 --
3.2 The Robustness of a CNN Template Set 25 --
3.3 Direct Design of Optimally Robust Templates 28 --
3.5 Making Templates Optimally Robust 39 --
3.6 Optimum Templates for a Specific CNN Implementation 40 --
4 CNN Settling Time 47 --
4.2 The Exact Approach 48 --
4.3 Analysis of Propagation-type Templates 54 --
4.4 Examples of Propagation-type Templates 59 --
4.5 Sensitivity to Parameter Deviations 69 --
4.6 Robustness vs. Processing Speed 74 --
5 Unification of Continuous- and Discrete-Time CNNs 83 --
5.1 Discrete-time CNNs 83 --
5.2 Delta Operator Based CNNs 84 --
5.3 Efficient Numerical Integration of CNNs 89 --
6 Stochastic Optimization 101 --
6.2 Genetic Optimization of CNNs 103 --
6.3 Other and Combined Approaches 114 --
6.4 Attacking the General Classification Problem 117 --
Appendix A. CNN Task Library 129 --
Appendix B. Simulation and Visualization of CNN Dynamics 133 --
B.2 Brief Characterization 134 --
B.3 Technical Information 135.
Responsibility: edited by Martin Hänggi and George S. Moschytz.
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