The issue of the loss of complete stability for a class of cellular neural networks (CNNs) is analyzed. It is shown that there are CNNs in this class for which a Hopf bifurcation is present, even if the interconnection matrix is arbitrarily close to some symmetric matrix. This shows that, in the general case, complete stability is not robust with respect to perturbations of nominal symmetric interconnection matrices
The paper considers a class of Full-Range (FR) cellular neural networks (CNNs) characterized by a fi...
This brief considers a class of delayed full-range (FR) cellular neural networks (CNNs) with uncerta...
The paper addresses robustness of complete stability with respect to perturbations of the interconne...
The issue of the loss of complete stability for a class of cellular neural networks (CNNs) is analyz...
Cellular neural networks (CNNs) are one of the most popular paradigms for real-time information proc...
This paper investigates the issue of robustness of complete stability of standard Cellular Neural Ne...
It is known that symmetric cellular neural networks (CNNs) are completely stable, i.e., each traject...
In this paper, the dynamical behavior of a class of third-order competitive cellular neural networks...
The paper investigates how the maximum gain of the neuron activation influences robustness of comple...
When the neuron interconnection matrix is symmetric, the standard Cellular Neural Networks (CNN's) i...
The paper considers a class of Full-Range (FR) cellular neural networks (CNNs) characterized by a fi...
This brief considers a class of delayed full-range (FR) cellular neural networks (CNNs) with uncerta...
The paper addresses robustness of complete stability with respect to perturbations of the interconne...
The issue of the loss of complete stability for a class of cellular neural networks (CNNs) is analyz...
Cellular neural networks (CNNs) are one of the most popular paradigms for real-time information proc...
This paper investigates the issue of robustness of complete stability of standard Cellular Neural Ne...
It is known that symmetric cellular neural networks (CNNs) are completely stable, i.e., each traject...
In this paper, the dynamical behavior of a class of third-order competitive cellular neural networks...
The paper investigates how the maximum gain of the neuron activation influences robustness of comple...
When the neuron interconnection matrix is symmetric, the standard Cellular Neural Networks (CNN's) i...
The paper considers a class of Full-Range (FR) cellular neural networks (CNNs) characterized by a fi...
This brief considers a class of delayed full-range (FR) cellular neural networks (CNNs) with uncerta...
The paper addresses robustness of complete stability with respect to perturbations of the interconne...