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: 20 Oct 2014 *
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