Linear phase FIR filter design using particle swarm optimization and genetic algorithms

Ababneh, Jehad; Bataineh, Mohammad H.

doi:10.1016/j.dsp.2007.05.011

Cited by 172 publications

(74 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“… Thus: (9) has been considered as fitness function in many literatures [11].The error to be minimized is defined as:…”

Section: E(ω)=w(ω) H (E )-H (E )mentioning

confidence: 99%

“…FIR digital filter is a basic computing unit of digital signal processing [1]and plays an important role in communication field and in the processing of digital signal. The design core of the FIR digital filter [2]centers on the optimization of multidimensional variable [3]. The design method of FIR digital filters are mainly: window function method, Chebyshev and frequency sampling method etc.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The Fir Digital Filter Design based on Iwpso

Hu¹,

Wang²,

Su³

2015

ijacsa

View full text Add to dashboard Cite

Abstract-The essence of finite impulse response (FIR) digital filter design is the problem of the parameter optimization. Namely the optimal parameters of FIR digital filter are the core of the design. In due to the traditional design method of FIR digital filter is not only accuracy not high but also sideband frequency is difficult to determine. Improve Weight Particle Swarm Optimization (IWPSO) to design FIR digital filter has less calculation and fast convergence speed. The simulation results also demonstrate that the IWPSO has better approximation properties and band-pass characteristics. what's more, the convergence of IWPSO algorithm made good results in filter design efficiency.

show abstract

“… Thus: (9) has been considered as fitness function in many literatures [11].The error to be minimized is defined as:…”

Section: E(ω)=w(ω) H (E )-H (E )mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Fir Digital Filter Design based on Iwpso

Hu¹,

Wang²,

Su³

2015

ijacsa

View full text Add to dashboard Cite

show abstract

“…The tests in [15,17,18] deal with FIR low-pass filters of order 20 and 30. To this end, the simulation was performed to design the low pass FIR filter with filter coefficient lengths of 21, 31 and 41.…”

Section: Basic Genetic Parametersmentioning

confidence: 99%

“…For the design of FIR filters, several researchers [15][16][17][18][19] have conducted interesting studies and performed comparisons between GAs and PSO. Their conclusion is that PSO is better than GA for the synthesis of 1-D FIR filters.…”

Section: Introductionmentioning

confidence: 99%

Potential of Particle Swarm Optimization and Genetic Algorithms for FIR Filter Design

Boudjelaba

Ros

Chikouche

2014

Circuits Syst Signal Process

View full text Add to dashboard Cite

“…[51,52] have used Hierarchical Genetic Algorithms to design and optimization of IIR filter structures. Use of Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) in the design of digital filters is described in [53].…”

Section: Introductionmentioning

confidence: 99%

Optimal Multiobjective Design of Digital Filters Using Taguchi Optimization Technique

Ouadi¹,

Bentarzi²,

Recioui³

2014

Journal of Electrical Engineering

View full text Add to dashboard Cite

The multiobjective design of digital filters using the powerful Taguchi optimization technique is considered in this paper. This relatively new optimization tool has been recently introduced to the field of engineering and is based on orthogonal arrays. It is characterized by its robustness, immunity to local optima trapping, relative fast convergence and ease of implementation. The objectives of filter design include matching some desired frequency response while having minimum linear phase; hence, reducing the time response. The results demonstrate that the proposed problem solving approach blended with the use of the Taguchi optimization technique produced filters that fulfill the desired characteristics and are of practical use.

show abstract

Linear phase FIR filter design using particle swarm optimization and genetic algorithms

Cited by 172 publications

References 16 publications

The Fir Digital Filter Design based on Iwpso

The Fir Digital Filter Design based on Iwpso

Potential of Particle Swarm Optimization and Genetic Algorithms for FIR Filter Design

Optimal Multiobjective Design of Digital Filters Using Taguchi Optimization Technique

Contact Info

Product

Resources

About