Title: Connected component detector using Dormand and Prince algorithm

Authors: S. Senthilkumar

Addresses: School of Mathematical Sciences, Universiti Sains Malaysia, Pulau Pinang-11800, Penang, Malaysia

Abstract: This paper deals with solving system of non-linear differential equation of cellular neural networks (CNNs) using different single-step numerical integration algorithms for connected component detector (CCD) along with bifurcation behaviour. Also, a simple cloning template for CNN is employed to detect the number of connected components of a vector in {+1, -1}N. Simulation results demonstrate that sixth order Dormand and Prince algorithm outperforms well in real time processing.

Keywords: cellular neural networks; nonlinear differential equations; CNNs; different Runge-Kutta methods; Dormand and Prince algorithm; ordinary differential equations; connected component detectors; CCD; simulation.

DOI: 10.1504/IJICT.2011.041747

International Journal of Information and Communication Technology, 2011 Vol.3 No.2, pp.180 - 194

Published online: 02 Aug 2011 *

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