An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum

Soodabeh Darzi, Sieh Kiong Tiong, Mohammad Tariqul Islam, Hassan Rezai Soleymanpour, Salehin Kibria

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

An experience oriented-convergence improved gravitational search algorithm (ECGSA) based on two new modifications, searching through the best experiments and using of a dynamic gravitational damping coefficient (α), is introduced in this paper. ECGSA saves its best fitness function evaluations and uses those as the agents' positions in searching process. In this way, the optimal found trajectories are retained and the search starts from these trajectories, which allow the algorithm to avoid the local optimums. Also, the agents can move faster in search space to obtain better exploration during the first stage of the searching process and they can converge rapidly to the optimal solution at the final stage of the search process by means of the proposed dynamic gravitational damping coefficient. The performance of ECGSA has been evaluated by applying it to eight standard benchmark functions along with six complicated composite test functions. It is also applied to adaptive beamforming problem as a practical issue to improve the weight vectors computed by minimum variance distortionless response (MVDR) beamforming technique. The results of implementation of the proposed algorithm are compared with some well-known heuristic methods and verified the proposed method in both reaching to optimal solutions and robustness.

Original languageEnglish
Article numbere0156749
JournalPLoS One
Volume11
Issue number7
DOIs
Publication statusPublished - 1 Jul 2016

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Beamforming
trajectories
Damping
Trajectories
Benchmarking
Heuristic methods
Function evaluation
methodology
Weights and Measures
Composite materials
Experiments
testing

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum. / Darzi, Soodabeh; Tiong, Sieh Kiong; Islam, Mohammad Tariqul; Rezai Soleymanpour, Hassan; Kibria, Salehin.

In: PLoS One, Vol. 11, No. 7, e0156749, 01.07.2016.

Research output: Contribution to journalArticle

Darzi, Soodabeh ; Tiong, Sieh Kiong ; Islam, Mohammad Tariqul ; Rezai Soleymanpour, Hassan ; Kibria, Salehin. / An experience oriented-convergence improved gravitational search algorithm for minimum variance distortionless response beamforming optimum. In: PLoS One. 2016 ; Vol. 11, No. 7.
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