Connected component detector using Dormand and Prince algorithm. (1st January 2011)

• Record Type: Journal Article
• Authors: Senthilkumar, S.
• Is Part Of: International journal of information and communication technology. Volume 3:Number 2(2011)
• Page Start: 180
• Page End: 194
• Publication Date: 2011-01-01
• Subjects: cellular neural/non-linear networks -- CNNs -- different Runge-Kutta methods -- Dormand and Prince algorithm -- ordinary differential equations -- connected component detector -- CCD; Information technology -- Periodicals; Computer science -- Periodicals; Telecommunication -- Periodicals; 004.05
• Languages: English
• ISSNs: 1466-6642

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.