Cellular Nonlinear/neural Network (CNN) technology is both a revolutionary concept and an
experimentally proven new computing paradigm. Analogic cellular computers based on …

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 …

For engineering applications that are based on nonlinear phenomena, novel information
processing systems require new methodologies and design principles. This perspective is …

We use the Cellular Neural Network (CNN) to study the pattern formation properties of large
scale spatially distributed systems. We have found that the Cellular Neural Network can …

In this paper the problem of the stability of Cellular Neural Networks (CNN's) and Delayed
Cellular Neural Networks (DCNN's) is addressed by means of Lyapunov functions …

Autonomous and nonautonomous Chua's circuits are of special significance in the study of
chaotic system modeling, chaos-based science and engineering applications. Since …

This paper gives a new sufficient condition for complete stability of a nonsymmetric cellular
neural network (CNN). The convergence theorem of the Gauss-Seidel method, which is an …

Two useful results concerning the equilibrium analysis of non‐symmetric cellular neural
networks (CNNs) are presented. First a new sufficient condition ensuring the existence of a …

The main results about stability of cellular neural networks (CNNs) are reviewed. Some of
them are extended and reformulated, with the purpose of providing to the CNN designer …

A complete study of non‐linear differential equations describing two‐cell cellular neural
networks (CNNs) is presented. the stability properties are investigated and the domains of …