scholarly journals Design of optimal linear phase FIR high pass filter using craziness based particle swarm optimization technique

2012 ◽  
Vol 24 (1) ◽  
pp. 83-92 ◽  
Author(s):  
Sangeeta Mandal ◽  
Sakti Prasad Ghoshal ◽  
Rajib Kar ◽  
Durbadal Mandal
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Linear Phase ◽  
Swarm Optimization ◽  
Pass Filter ◽  
High Pass Filter ◽  
Optimal Linear ◽  
Particle Swarm Optimization Technique ◽  
High Pass

Improved Particle Swarm Optimization (PSO) for Performance Optimization of Electronic Filter Circuit Designs

2012 ◽  
Vol 229-231 ◽  
pp. 1643-1650
Author(s):  
Chong Woon Kien ◽  
Neoh Siew Chin
Keyword(s):  
Particle Swarm Optimization ◽  
Performance Optimization ◽  
Particle Swarm ◽  
Design Parameters ◽  
Pass Band ◽  
Swarm Optimization ◽  
Pass Filter ◽  
High Pass Filter ◽  
And Performance ◽  
High Pass

This article discusses and analyzes particle swarm optimization (PSO) approach in the design and performance optimization of a 4th-order Sallen Key high pass filter. Three types of particle swarm features are studied: basic PSO, PSO with regrouped particles (PSO-RP) and PSO with diversity embedded regrouped particles (PSO-DRP). PSO-RP and PSO-DRP are proposed to solve the stagnation problem of basic PSO. Based on the developed PSO approaches, LTspice is employed as the circuit simulator for the performance investigation of the designed filter. In this paper, 12 design parameters of the Sallen Key high pass filter are optimized to satisfy the required constraints and specifications on gain, cut-off frequency, and pass band ripples. Overall results show that PSO with diversity embedded regrouped particles improve the conventional search of basic PSO and has managed to achieve the design objectives.

Design of Linear Phase FIR Low Pass Filter Using Mutation-Based Particle Swarm Optimization Technique

2020 ◽  
pp. 344-358
Author(s):  
Taranjit Kaur ◽  
Balwinder Singh Dhaliwal
Keyword(s):  
Particle Swarm Optimization ◽  
Filter Design ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Linear Phase ◽  
Swarm Optimization ◽  
Local Optima ◽  
Response Characteristics ◽  
Low Pass ◽  
Particle Swarm Optimization Technique

This chapter presents a mutation-based particle swarm optimization (PSO) approach for designing a linear phase digital low pass FIR filter (LPF). Since conventional gradient-based methods are susceptible to being trapped in local optima, the stochastic search methods have proven to be effective in a multi-dimensional non-linear environment. In this chapter, LPF with 20 coefficients has been designed. Since filter design is a multidimensional optimization problem, the concept of mutation helps in maintaining diversity in the swarm population and thereby efficiently controlling the local search and convergence to the global optimum solution. Given the filter specifications to be realized, the Mutation PSO (MPSO) tries to meet the ideal frequency response characteristics by generating an optimal set of filter coefficients. The simulation results have been compared with basic PSO and state of artworks on filter design. The results justify that the proposed technique outperforms not only in convergence speed but also in the quality of the solution obtained.

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