LEARNING ALGORITHM FOR THE DESIGN OF DIGITAL CELLULAR NEURAL NETWORK
用于数字式细胞神经网络设计的学习算法

The application of cellular neural networks is determined by its templates. In accordance with the application of digital cellular neural network the author proposed before, a method for the design of its templates, i.e. inequalities construcion method, is given and a supervised learning algorithm is proposed based on the relaxation method. The learning algorithm provides theoretical basis for the design of DCNN. Simulation results on examples such as connected component detection shows the effectiveness and feasibility of the algorithm.