Digital FIR Filter Design by PSO and its variants Attractive and Repulsive PSO(ARPSO) & Craziness based PSO(CRPSO)

Digital filters play a major role in signal processing that are employed in many applications such as in control systems, audio or video processing systems, noise reduction applications and different systems for communication. In this regard, FIR filters are employed because of frequency stability and linearity in their phase response. FIR filter design requires multi-modal optimization problems. Therefore, PSO (Particle Swarm Optimization) algorithm and its variants are more adaptable techniques based upon particles’ population in the search space and a great option for designing FIR filter. PSO and its different variants improve the solution characteristic by providing a unique approach for updating the velocity and position of the swarm. An optimized set of filter coefficient is produced by PSO and its variant algorithms which gives the optimized results in passband and stopband. In this research paper, Digital FIR filter is effectively designed by using PSO Algorithm and its two variants ARPSO and CRPSO in MATLAB. The outcomes prove that the filter design technique using CRPSO is better than filter design by PM algorithm. PSO and ARPSO Algorithms in the context of frequency spectrum and RMS error.

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An Improved Particle Swarm Optimization algorithm for FIR filter design

2013 IEEE 20th International Conference on Electronics, Circuits, and Systems (ICECS) ◽

10.1109/icecs.2013.6815404 ◽

2013 ◽

Cited By ~ 1

Author(s):

Xia Yuanhai

Keyword(s):

Particle Swarm Optimization ◽

Optimization Algorithm ◽

Particle Swarm Optimization Algorithm ◽

Filter Design ◽

Particle Swarm ◽

Fir Filter ◽

Swarm Optimization ◽

Improved Particle Swarm Optimization ◽

Fir Filter Design

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FIR Filter Design using Finfets at 22nm Technology

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.a2018.129219 ◽

2019 ◽

Vol 9 (2) ◽

pp. 1292-1295

Keyword(s):

Video Processing ◽

Filter Design ◽

Finite Impulse Response ◽

Digital Signal ◽

Fir Filter ◽

Fir Filters ◽

Short Channel ◽

Channel Effects ◽

Complex Circuits ◽

Fir Filter Design

Finite Impulse Response (FIR) filters are the most significantdevice in digital signal processing.In many Digital Signal Processing applications like wireless communication, image and video processing FIR filters are used.Digital FIR filters primarily consists of multipliers, adders and delay elements. Area, power optimization and speed are the key design metrics of FiniteImpulse Response filter.As more electronic devices are battery operated, power consumption constraint becomes a major issue. Multipliers are the core of FIR filters. They consume a lot of energy and are generally complex circuits. With each new process technologies, the short channel effects limit the performance of FIR filters at nano regime. Various architectures have been proposed to enhance the performance of FIR filter. In this paper, FIR filter is designed using FINFETs at 22nm technology using Hspice software.

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Efficient and Accurate Optimal Linear Phase FIR Filter Design Using Opposition-Based Harmony Search Algorithm

The Scientific World JOURNAL ◽

10.1155/2013/320489 ◽

2013 ◽

Vol 2013 ◽

pp. 1-16 ◽

Cited By ~ 23

Author(s):

S. K. Saha ◽

R. Dutta ◽

R. Choudhury ◽

R. Kar ◽

D. Mandal ◽

...

Keyword(s):

Filter Design ◽

Search Algorithm ◽

Harmony Search ◽

Search Space ◽

Fir Filter ◽

Harmony Search Algorithm ◽

Optimization Techniques ◽

Fir Filters ◽

Linear Phase ◽

Fir Filter Design

In this paper, opposition-based harmony search has been applied for the optimal design of linear phase FIR filters. RGA, PSO, and DE have also been adopted for the sake of comparison. The original harmony search algorithm is chosen as the parent one, and opposition-based approach is applied. During the initialization, randomly generated population of solutions is chosen, opposite solutions are also considered, and the fitter one is selected asa prioriguess. In harmony memory, each such solution passes through memory consideration rule, pitch adjustment rule, and then opposition-based reinitialization generation jumping, which gives the optimum result corresponding to the least error fitness in multidimensional search space of FIR filter design. Incorporation of different control parameters in the basic HS algorithm results in the balancing of exploration and exploitation of search space. Low pass, high pass, band pass, and band stop FIR filters are designed with the proposed OHS and other aforementioned algorithms individually for comparative optimization performance. A comparison of simulation results reveals the optimization efficacy of the OHS over the other optimization techniques for the solution of the multimodal, nondifferentiable, nonlinear, and constrained FIR filter design problems.

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