Realization of Delayed Cellular Neural Network model ON FPGA
Barış Karakaya, Vedat Çelik, Arif Gülten · 2018
This paper presents realization of a Delayed Cellular Neural Network (DCNN) on field programmable gate array (FPGA). The network has two cells and a strange attractor has been found in a system described by a differential equation. In the implementation stage, Xilinx System Generator (XSG) is used and discrete time model of the network is implemented on Xilinx Spartan 3e XC3S1600e FPGA development board. The realization of DCNN on FPGA chip provides an opportunity to make the system suitable for high operating frequency applications, such as secure communication and cryptographic systems.