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Improved sufficient convergence condition for the discrete-time cellular neural networks

In this paper, we derive an improved sufficient convergence condition for discrete-time cellular neural networks (DTCNN) using the positive semidefinite (PSD) constraint and the boundary condition of DTCNN. The experimental results confirm that the derived condition offers a wider convergence range than the convergence condition of Fruehauf (1992). The new condition does not depend on the type of the nonlinear output function of the DTCNN.