On the complete stability of nonsymmetric cellular neural networks
Norikazu Takahashi, Leon Ong Chua · IEEE Transactions on Circuits and Systems I Fundamental Theory and Applications · 1998
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 iterative technique for solving a linear algebraic equation, plays an important role in our proof. It is also shown that the existence of a stable equilibrium point does not imply complete stability of a nonsymmetric CNN.