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Hole-Filler Cellular Neural Network Simulation by RKGHM(5,5)

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Abstract

The construction of two novel integration algorithms are proposed by formulating Runge-Kutta embedded techniques based on geometric mean (GM) coupled with contra-harmonic mean and harmonic mean with error control under general cellular nonlinear network paradigm. This paper attempts to analyze the performance of hole-filling cellular nonlinear network arrays through potential behaviour of newly proposed versatile algorithm. A promising simulation result shows that more quantitative analysis has been carried out to clearly visualize the goodness and robustness of the proposed embedded algorithms for hole-filler.

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  1. School of Mathematical Sciences, Universiti Sains Malaysia, Pulau Pinang, 11800, Penang, Malaysia

    S. Senthilkumar

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  1. S. Senthilkumar
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Correspondence to S. Senthilkumar.

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Senthilkumar, S. Hole-Filler Cellular Neural Network Simulation by RKGHM(5,5). J Math Imaging Vis 43, 194–205 (2012). https://doi.org/10.1007/s10851-011-0300-4

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