An annealing method for cellular neural networks

Abstract

The spurious minima in optimizing operation is one of the difficulty for Lyapunov function. In this paper, novel lossless image coding method based on lifting scheme using discrete-time cellular neural networks (DT-CNNs) with annealing approach is proposed. In the proposed, the image prediction of lifting scheme is implimented by DT-CNNs solving the nonlinear optimization problem of Lyapunov energy function. Since the stability point of DT-CNNs energy function is depends to the initial state value of cells, an annealing effect of adaptive chaotic noise is used to avoid the difficulty of global asymptotical stability of DT-CNNs dynamics. The experimental results show that the proposed method produces better results than those of conventional lossless image coding methods.