A Hybrid Artificial Rabbits Optimization Algorithm to Design FIR Filter and its FPGA Implementation

This paper proposes an improved model of a newly emerged biologically motivated meta-heuristic Artificial Rabbits Optimization (ARO) algorithm. The ARO algorithm is hybridized with Particle Swarm Optimization (PSO) algorithm to enhance the local exploitation strategy of standard ARO. The proposed ARPSO algorithm is used to optimize the coefficients of Finite Impulse Response (FIR) filter of order 20 for low-pass (LP) and high-pass (HP) design. The proposed filters are then compared with few recently reported algorithms to show better performance parameter values. Finally, both the LP and HP design of FIR filters are implemented in the FPGA platform in Spartan 6 board with Xilinx ISE Design suite 14.7. The FPGA model is also compared with some recent algorithms to verify its robustness.