Robust decomposition with guaranteed robustness for cellular neural networks implementing an arbitrary Boolean function

Given a general Boolean function, an algorithm is proposed in this paper to find a sequence of robust uncoupled cellular neural networks, with logic operators as the conjunctions, implementing the given Boolean function. Each resulting robust uncoupled cellular neural network in the decomposition has a margin greater than or equal to a pre-specified value. For reasonable robustness levels, the proposed algorithm usually requires lesser number of searching templates and provides faster execution than those by using other similar methods. Furthermore, a mechanism for practical tradeoff between the guaranteed robustness and the complexity in terms of the number of terms in the decomposition is provided in our proposed algorithm.