Cellular neural networks : theory and applications
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Bibliographic Information
Cellular neural networks : theory and applications
Nova Science Publishers, c2004
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Includes bibliographical references and index
Description and Table of Contents
Description
Cellular Neural Networks (CNN's) were introduced in 1988 by L O Chua and L Yang as a novel class of information processing systems, which possesses some of the key features of Neural Networks and which has important potential applications in such areas as image processing and pattern recognition. Many complex computational problems can be formulated, as well-defined tasks where the signal values are placed on a regular geometric 2-D or 3-D grid, and the direct interaction between signal values are limited within a finite local neighbourhood. CNN is an analogue dynamic processor array, which reflects just this property: the processing elements interact directly within a finite local neighbourhood. The purpose of the book is to present the recent results in the basic concepts of dynamics, stability analysis and CNN models of some partial differential equations.
Table of Contents
- CONTENTS: Preface
- Introduction to Cellular Neural Networks
- Theory of Cellular Neural Networks: Mathematical Point of View
- Stability Analysis of Bidirectional Associative Memory CNNs with time delays
- On the Dynamics of Some Classes of Cellular Neural Networks
- Spatio-Temporal Phenomena in Two-dimensional Cellular Nonlinear Networks
- Travelling Waves in FitzHugh-Nagumo Cellular Neural Network Model
- CNN Applications in Modeling and Solving Non-Electrical Problems
- CNN for Obstacle Detection in Stereo Vision Imagery
- Object Tracking and Exact Colour Reproduction for Medical Imaging
- Criteria for Trained Neural Networks with Appliance in Passive Radiolocation
- Index.
by "Nielsen BookData"
