Performance Analysis of Low Pass FIR Filter Design using Dynamic and Adjustable Particle Swarm Optimization Techniques
Kaushal Kishor Tripathi, Mohd Suhaib Kidwai, Imran Ullah Khan · 2021
Digital filters have wide extension in control system, sound system, communication, video processing, and clinical/biomedical applications. Exact linear phase and multirate activity can be accomplished with digital executions. In this paper digital filters design problem that involves multiple, often conflicting, design criteria and specifications are discussed. Tracking down an optimum filter configuration is the fundamental goal in this work. If simple/analytic iterative methods is used it will lead to sub-optimal designs. So, an optimization-based method is needed. A low pass finite impulse response (LPFIR) filter optimal design can be achieved by Particle Swarm Optimization and/or dynamic adjustable PSO (DAPSO). In this paper DAPSO algorithms are discussed for different error function. The DAPSO is an improved version of PSO. It proposes swarm updating and velocity vector and hence the solution quality is improved.