Abstract / truncated to 115 words (read the full abstract)

Cellular Neural Networks are characterized by simplicity of operation. The network consists of a large number of nonlinear processing units; called cells; that are equally spread in the space. Each cell has a simple function (sequence of multiply-add followed by a single discrimination) that takes an element of a topographic map and then interacts with all cells within a specified sphere of interest through direct connections. Due to their intrinsic parallel computing power, CNNs have attracted the attention of a wide variety of scientists in, e.g., the fields of image and video processing, robotics and higher brain functions. Simplicity of operation together with the local connectivity gives CNNs first-hand advantages for tiled VLSI implementations with ... toggle 10 keywords

cellular neural network – discrete-time cellular neural network – field- programmable gate-array – circuit switching – network on chip – serialized broadcast – switched broadcast – velocity measurement – vein feature extraction – image processing

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