Image processing applications via time-multiplexing cellular neural network simulator with numerical integration algorithms

Abstract

A novel approach to simulate cellular neural networks (CNN) is presented in this paper. The approach, time-multiplexing simulation, is prompted by the need to simulate hardware models and test hardware implementations of CNN. For practical applications, due to hardware limitations, it is impossible to have a one-to-one mapping between the CNN hardware processors and all the pixels of the image. This simulator provides a solution by processing the input image block by block, with the number of pixels in a block being the same as the number of CNN processors in the hardware. The algorithm for implementing this simulator is presented along with popular numerical integration algorithms. Some simulation results and comparisons are also presented.

Keywords:

• cellular neural networks
• Euler algorithm
• RK–Gill algorithm
• RK–Butcher algorithm
• ordinary differential equations

CCS Category :

• G.1.7