Implementation of Two Cell Non-Autonomous CNN Model on FPGA

Abstract

This paper presents implementation of a chaotic Cellular Neural Network (CNN) on Field Programmable Gate Array (FPGA). The network has two non-autonomous cells and exhibits chaotic behavior. In the implementation stage, Verilog Hardware Description Language (HDL) is used and discrete time model of the network is coded on Xilinx ISE Design Suite 13.2. It seems that the chaotic attractor can be used as entropy source or short key (seed) of chaos based random number generator design.