An Improved IIR Filter Design using Artificial Rabbits Optimization Algorithm and its FPGA Implementation

This paper presents a meta-heuristic optimization algorithm known as Artificial Rabbits Optimization (ARO) to get the optimal set of infinite impulse response (IIR) filter coefficients. Application of the ARO algorithm to design two real-life examples is used for performance testing. The proposed algorithm is simulated to get the coefficients of different types of linear and non-linear (with noise and without noise) problems with similar order and lower order, and the simulated results are compared with few recent optimization algorithms such as Salp Swarm Algorithm (SSA), Whale Optimization Algorithm (WOA), and Dragonfly Algorithm (DA). The proposed algorithm is much faster and efficient than the numerous standard algorithms. The Proposed ARO algorithm demonstrates a lower Mean Square Error (MSE) and superior convergence speed as compared to the other optimization techniques examined herein. FPGA implementation is performed to design IIR filters where ARO shows better performance.