Raster simulation using advanced fuzzy cellular non-linear network
Sukumar Senthilkumar · International Journal of Autonomous and Adaptive Communications Systems · 2010
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.