Title: Raster simulation using advanced fuzzy cellular non-linear network

Authors: Sukumar Senthilkumar

Addresses: Department of Mathematics, National Institute of Technology, Tiruchirappalli 620 015, Tamilnadu, India

Abstract: In this framework, a non-linear network structure known as fuzzy cellular neural network (FCNN) of type II is reported by integrating fuzzy operations with the classical cellular neural network (CNN) structure and it is an extension of the cellular non-linear network from classical to fuzzy sets (FSs). Type II FCNN is implemented to detect the edges of an object through raster scheme efficiently. The functional behaviour of the simulator is to perform raster simulation for any kind as well as any size of input image using the two newly proposed efficient numerical techniques. An efficient pseudo code for exploiting the latency properties of type II FCNN along with well-known RK-fourth-order embedded numerical integration algorithms is presented. Simulation results and comparison have also been presented to show the efficiency of the newly introduced numerical integration algorithm.

Keywords: type II FCNN; fuzzy cellular neural networks; numerical integration; raster simulation; edge detection; fuzzy sets; fuzzy logic; cellular nonlinear networks.

DOI: 10.1504/IJAACS.2010.035549

International Journal of Autonomous and Adaptive Communications Systems, 2010 Vol.3 No.4, pp.464 - 478

Published online: 30 Sep 2010 *

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