Title: An improved fuzzy cellular neural network (IFCNN) for an edge detection based on parallel RK(5,6) approach

Authors: Sukumar Senthilkumar; Abd Rahni Mt Piah

Addresses: School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM Pulau Pinang, Malaysia. ' School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM Pulau Pinang, Malaysia

Abstract: Parallel RK(5,6) algorithms are employed to validate the potential behaviour under improved fuzzy cellular neural network paradigm for an edge detection problem is the novelty of this paper. The function of the simulator is capable of performing raster fuzzy cellular neural network simulation for any kind as well as any size of input image. The raster pseudo code exploits the latency properties of improved fuzzy cellular neural network coupled with different parallel numerical integration algorithms. Results provide a better understanding about single layer/raster behaviour simulation.

Keywords: numerical integration; fuzzy cellular neural networks; single layer; raster pseudo code; edge detection; simulation; ordinary differential equations; ODEs; latency.

DOI: 10.1504/IJCSYSE.2012.044745

International Journal of Computational Systems Engineering, 2012 Vol.1 No.1, pp.70 - 78

Published online: 23 Aug 2014 *

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