Designing of 2d-IIR Filter Using a Fused ESMA-Pelican Optimization Algorithm (FEPOA)

Abstract

Many Digital Signal Processing (DSP) applications and electronic gadgets today require digital filtering. Different optimization algorithms have been used to obtain fast and improved results. Several researchers have used Enhanced Slime Mould Algorithm for designing the 2D IIR filter. However, it is observed that the Enhanced Slime Mould Algorithm did not achieve a better solution structure and had a slower convergence rate. In order to overcome the issue a fused ESMA-pelican Optimization Algorithm (FEPOA) is utilized for designing the 2D IIR filter which incorporates the pelican Optimization Algorithm with the Enhanced slime Mould Algorithm (ESMA). At first, the Chaotic Approach is utilized to initialize the population which provides the high-quality population with excellent population diversity, after that the position of population members is to identify and correct the individual in the boundary search region. After that, by the pelican Tactical Approach is to examine the search space and exploration power of the FEPOA, then the Fitness is calculated randomly, and the best solution will be upgraded and then moved towards the iterations. It repeats the FEPOA phases until the execution completes. Then the best solution gives the optimal solution, which enhances the speed of convergence, convergence accuracy and the performances of FEPOA. The FEPOA is then implemented in the IIR filter to improve the overall filter design. The results provided by FEPOA accomplish the necessary fitness and best solution for 200 iterations, and the amplitude response will achieve the maximum value for =2,4,8 as well as the execution time of 3.0158s, which is much quicker than the other Genetic Algorithms often used for 2D IIR filters.

Keywords

• fepoa
• iir filter
• population member
• fir filter
• chaotic approach
• pelican's tactical approach