FPGA based Synthesize of PSO Algorithm and its Area-Performance Analysis

Bharat Lal Harijan,Burhan Aslam,Farrukh Shaikh,Tayab Din,Imtiaz Hussain

doi:10.14569/ijacsa.2018.090639

Abstract

Digital filters are the most significant part of signal processing that are used in enormous applications such as speech recognition, acoustic, adaptive equalization, and noise and interference reduction. It would be of great benefit to implement adaptive FIR filter because of self-optimization property, linearity and frequency stability. Designing FIR filter involves multi-modal optimization problems whereas conservative gradient optimization technique is not useful to design the filter. Hence, Particle Swarm Optimization (PSO) algorithm is more flexible and optimization technique based on population of particles in search space and alternative approach for linear phase FIR filter design. PSO improves the solution characteristic by giving a novel method for updating swarm’s position and velocity vector. Set of optimized filter coefficients will be generated by PSO algorithm. In this paper, PSO based FIR Low pass filter is efficiently designed in MATLAB and further Xilinx System Generator tool is used to efficiently design, synthesize and implement FIR filter in FPGA using SPARTEN 3E kit. For an example specifications, output of PSO algorithm is obtained that is set of optimized coefficients whose response is approximating to the ideal response. Hence, functional verification of the proposed algorithm has been performed and the error between obtained filter and ideal filter is minimized successfully. This work demonstrates the effectiveness of the PSO algorithms in parallel processing environment as compared to the Remez Exchange algorithm.

Highlights

Digital filters enable us to pass some frequencies unaltered, while totally blocking others
An exactly linear phase response can be generated by finite Impulse response (FIR) Filter and no any phase distortion or noise present in the output signal which is required in wide verity of telecommunication applications i.e. echo cancellation, noise and interface reduction, speech or image encoding
The mean square error is computed using (3), and obtained Error = 0.3447933 when filter designed by Remez Exchange Algorithm and Error = 0.06442020 while filter designed by Particle Swarm Optimization (PSO) algorithm

Summary

INTRODUCTION

Digital filters enable us to pass some frequencies unaltered, while totally blocking others. Like Genetic Algorithm [3], Particle Swam Optimization algorithm [4], Differential Evolution [5], Artificial Bee Colony [6] are implemented for filer design. These methods showed themselves fairly effective by providing better control of performance constraints in addition to high stopband attenuation. Designing FIR low pass filter using traditional methods require more coefficients if sharp cutoff or no phase distortion is required and actual response H(Ω) is not more approximating to desired frequency response Hd(Ω) within a given specification in magnitude and phase [11], [12]. This work will culminate with development of single-bit ternary PSO algorithm

FIR Low Pass Filter Design

Designing Steps

FIR LP FILTER DESIGN UISNG XILINX SYSTEM GENERATOR

SIMULAITON RESULTS AND DISCUSSION

CONCLUSION