Automatic Robust Designs of Template Parameters for a Type of Uncoupled Cellular Neural Networks

This paper proposes a robust design theorem for a kind of uncoupled cellular neural/nonlinear networks (CNNs) in aim to process images with some specific image properties. A novel algorithm scheme is introduced to automatically determine the required image parameters given in the theorem, and implement image processing. Using the proposed theorem designs a convex corner detection, CNN template, and some edge detection CNN templates. Four image processing examples are given. Comparing the edge detection algorithms “Sobel,” “Prewitt,” “Roberts,” and “Canny” with our algorithm shows that the presented algorithm has promising results.

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