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Cellular neural networks : dynamics and modelling

Cellular neural networks : dynamics and modelling

Material type
단행본
Personal Author
Slavova, Angela.
Title Statement
Cellular neural networks : dynamics and modelling / by Angela Slavova.
Publication, Distribution, etc
Dordrecht, The Netherlands ;   Boston :   Kluwer Academic Publishers ,   c2003.  
Physical Medium
x, 220 p. : ill. ; 25 cm.
Series Statement
Mathematical modelling--theory and applications ; v. 16
ISBN
140201192X (hc. : alk. paper)
Bibliography, Etc. Note
Includes bibliographical references (p. 203-216) and index.
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001 000045468606
005 20080908151119
008 050317s2003 ne a b 001 0 eng
010 ▼a 2003044506
020 ▼a 140201192X (hc. : alk. paper)
035 ▼a (KERIS)BIB000009765255
040 ▼a DLC ▼c DLC ▼d DLC ▼d 222001 ▼d 244002
042 ▼a pcc
050 0 0 ▼a QA76.87 ▼b .S618 2003
082 0 0 ▼a 006.3/2 ▼2 22
090 ▼a 006.32 ▼b S631c
100 1 ▼a Slavova, Angela.
245 1 0 ▼a Cellular neural networks : ▼b dynamics and modelling / ▼c by Angela Slavova.
260 ▼a Dordrecht, The Netherlands ; ▼a Boston : ▼b Kluwer Academic Publishers , ▼c c2003.
300 ▼a x, 220 p. : ▼b ill. ; ▼c 25 cm.
440 0 ▼a Mathematical modelling--theory and applications ; ▼v v. 16
504 ▼a Includes bibliographical references (p. 203-216) and index.

Holdings Information

No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
No. 1 Location Sejong Academic Information Center/Course Reserves/ Call Number 정보수학과 006.32 S631c Accession No. 151261569 Availability Loan can not(reference room) Due Date Make a Reservation Service

Contents information

Table of Contents

Preface. 1: Basic theory about CNNs. 1.1. Introduction to the CNN paradigm. 1.2. Main types of CNN equations. 1.3. Theorems and results on CNN stability. 1.4. Examples. 2: Dynamics of nonlinear and delay CNNs. 2.1. Nonlinear CNNs. 2.2. CNN with delay. 2.3. Examples. 3: Hysteresis and chaos in CNNs. 3.1. CNNs with hystersis in the feedback system. 3.2. Nonlinear CNNs with hysteresis in the output dynamics. 3.3. Feedback and hysteresis. 3.4. Control of chaotic CNNs. 4: CNN modelling in biology, physics and ecology. 4.1. Modelling PDEs via CNNs. 4.2. CNN model of Sine-Gordon equation. 4.3. CNN model of FitzHugh-Nagumo equation. 4.4. CNN model of Fisher's equation. 4.5. CNN model of Brusselator equation. 4.6. CNN model of Toda Lattice equation. 4.7. Lotka-Volterra equation and its CNN model. 5: Appendix A: Topological degree method. 6: Appendix B: Hysteresis and its models. 7: Appendix C: Describing function method and its application for analysis of Cellular Neural Networks. References. Index.


Information Provided By: : Aladin

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