Design of linear phase low pass FIR filter using restart particle swarm optimization

2016 ◽  
Author(s):  
Himanshu Gupta ◽  
Deepak Mandloi ◽  
Anand Jat ◽  
Arpit Gupta ◽  
Prabhakar Ojha
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Fir Filter ◽  
Linear Phase ◽  
Swarm Optimization ◽  
Low Pass

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.

scholarly journals Simultaneous Design of Low-Pass Filter with Impedance Matching Transformer for SONAR Transducer Using Particle Swarm Optimization

Energies ◽  
2019 ◽  
Vol 12 (24) ◽  
pp. 4646
Author(s):  
Jae-Hyuk Choi ◽  
Hyung-Soo Mok
Keyword(s):  
Particle Swarm Optimization ◽  
Impedance Matching ◽  
Particle Swarm ◽  
Acoustic Signals ◽  
Design Methods ◽  
Swarm Optimization ◽  
Pass Filter ◽  
Low Pass Filter ◽  
Simultaneous Design ◽  
Low Pass

Sound navigation and ranging (SONAR) systems detect a target in the front direction by using acoustic signals. A switching-type power conversion system is used to improve power efficiency, and an impedance matching circuit is used to decrease reactive power. A low-pass filter is used to improve the quality of acoustic signals. To achieve the desired voltage level for a SONAR transducer, a transformer is connected in series with a low-pass filter. In conventional design methods, design value errors occur because the components are designed independently and later combined. Moreover, if parameters that considerably impact operating characteristics are ignored in the design process, these errors will increase. Hence, time and cost losses are incurred during refabrication because operational characteristics differ from design values. To solve this problem, this study proposes the simultaneous design of a low-pass filter and impedance matching circuit, which includes critical design parameters, utilizing the particle swarm optimization algorithm. Moreover, conventional design methods were examined, and the superiority of the proposed design method to conventional methods was verified through analyses and experiments in terms of overall impedance phase and filter blocking characteristics.

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