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The field of cellular neural networks (CNNs) is of growing importance in non linear circuits and systems and it is maturing to the point of becoming a new area of study in general nonlinear theory. CNNs emerged through two semi nal papers co-authored by Professor Leon O. Chua back in 1988. Since then, the attention that CNNs have attracted in the scientific community has been vast. For instance, there are international workshops dedicated to CNNs and their applications, special issues published in both the International Journal of Circuit Theory and in the IEEE Transactions on Circuits and Systems, and there are also Associate Editors appointed in the latter journal especially for the CNN field. All of this bears witness the importance that CNNs are gaining within the scientific community. Without doubt this book is a primer in the field. Its extensive coverage provides the reader with a very comprehensive view of aspects involved in the theory and applications of cellular neural networks. The authors have done an excellent job merging basic CNN theory, synchronization, spatio temporal phenomena and hardware implementation into eight exquisitely written chapters. Each chapter is thoroughly illustrated with examples and case studies. The result is a book that is not only excellent as a professional reference but also very appealing as a textbook. My view is that students as well professional engineers will find this volume extremely useful.
List of contents
I. Circuit Theory and Applications of CNNs.- 1. CNN Basics.- 2. Some Applications of CNNs.- 3. The CNN as a Generator of Nonlinear Dynamics.- 4. Synchronization.- 5. Spatio-temporal Phenomena.- 6. Experimental CNN Setup and Applications to Motion Control.- II. Implementation and Design.- 7. A Four Quadrant S2I Switched-Current Multiplier.- 8. A One-Dimensional Discrete-Time CNN Chip for Audio Signal Processing.- A. Mathematical Background.- A.1 Topology.- A.2 Operations and Functions.- A.3 Matrices.- A.4 Dimension.- A.5 Dynamical Systems: Basic Definitions.- A.6 Steady-State Behavior.- A.6.1 Classification of Asymptotic Behavior.- A.7 Stability.- A.7.1 Stability of equilibrium points.- A.7.2 Stability of Limit Cycles.- A.7.3 Lyapunov Exponents.- A.8 Topological Equivalence and Conjugacy, Structural Stability and Bifurcations.- A.9 Silnikov Method.- A.10 Particular Results for Two-Dimensional Flows.- B. Library of Templates.- References.
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From the reviews:
"The book is divided into eight chapters and each of them guides us through one area where the CNNs can be used ... . I recommend the publication to everybody, who is interested in the CNN and its application and implementation, but also to those who face some of the technologies described there, such as nonlinear dynamics, synchronization, signal processing or motion control, because the CNN can show a quite novel and beneficial point of view." (Václav Dekanovský, Neural Network World, Vol. 15 (5), 2005)
