Abstract

Fuzzy cellular neural networks (FCNN) are novel classes of cellular neural networks. In this paper, some typical applications of FCNN are presented, such as gray-scale mathematical morphology and fuzzy inference edge detection. FCNN is a generalization of CNN by using fuzzy operations in the synaptic law calculation allowing us to implement the low level information processing capability of CNNs with the high level information processing capability, such as image understanding, of fuzzy systems. The FCNN structures are based on the uncertainties in human cognitive processes and in modeling neural systems, and provide an interface between the human expert and the classical CNN.

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