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Image processing applications via time-multiplexing cellular neural network simulator with numerical integration algorithms

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INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS 2010年第4期87卷 840-848页

作者： Murugesh, V. European Univ Lefke Dept Comp Engn Trnc Mersin Turkey

A novel approach to simulate cellular neural networks (CNN) is presented in this paper. The approach, time-multiplexing simulation, is prompted by the need to simulate hardware models and test hardware implementations of CNN. For practical applications, due to hardware limitations, it is impossible to have a one-to-one mapping between the CNN hardware processors and all the pixels of the image. This simulator provides a solution by processing the input image block by block, with the number of pixels in a block being the same as the number of CNN processors in the hardware. The algorithm for implementing this simulator is presented along with popular numerical integration algorithms. Some simulation results and comparisons are also presented.

关键词： cellular neural networks Euler algorithm rk-gill algorithm rk-Butcher algorithm ordinary differential equations

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Raster cellular neural network simulator for image processing applications with numerical integration algorithms

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INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS 2009年第7期86卷 1215-1221页

作者： Murugesh, V. European Univ Lefke Dept Comp Engn Gemikonagi Lefke Turkey

In this paper, a universal simulator for cellular neural network (CNN) is presented. This simulator is capable of performing Raster simulation for any size of input image, and thus is a powerful tool for researchers investigating potential applications of CNN. This paper reports the latency properties of CNNs along with popular numerical integration algorithms;results and comparisons are also presented.

关键词： cellular neural networks Euler algorithm rk-gill algorithm rk-Butcher algorithm ordinary differential equations

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