Gravitation search algorithm: Application to the optimal IIR filter design
This paper presents a global heuristic search optimization technique known as Gravitation Search Algorithm (GSA) for the design of 8th order Infinite Impulse Response (IIR), low pass (LP), high pass (HP), band pass (BP) and band stop (BS) filters considering various non-linear characteristics of the...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2014-01-01
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| Series: | Journal of King Saud University: Engineering Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1018363912000517 |
| _version_ | 1819094438921633792 |
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| author | Suman Kumar Saha Rajib Kar Durbadal Mandal S.P. Ghoshal |
| author_facet | Suman Kumar Saha Rajib Kar Durbadal Mandal S.P. Ghoshal |
| author_sort | Suman Kumar Saha |
| collection | DOAJ |
| description | This paper presents a global heuristic search optimization technique known as Gravitation Search Algorithm (GSA) for the design of 8th order Infinite Impulse Response (IIR), low pass (LP), high pass (HP), band pass (BP) and band stop (BS) filters considering various non-linear characteristics of the filter design problems. This paper also adopts a novel fitness function in order to improve the stop band attenuation to a great extent. In GSA, law of gravity and mass interactions among different particles are adopted for handling the non-linear IIR filter design optimization problem. In this optimization technique, searcher agents are the collection of masses and interactions among them are governed by the Newtonian gravity and the laws of motion. The performances of the GSA based IIR filter designs have proven to be superior as compared to those obtained by real coded genetic algorithm (RGA) and standard Particle Swarm Optimization (PSO). Extensive simulation results affirm that the proposed approach using GSA outperforms over its counterparts not only in terms of quality output, i.e., sharpness at cut-off, smaller pass band ripple, higher stop band attenuation, but also the fastest convergence speed with assured stability. |
| first_indexed | 2024-12-21T23:27:25Z |
| format | Article |
| id | doaj.art-3e66f522d90e46d19c970fff39839868 |
| institution | Directory Open Access Journal |
| issn | 1018-3639 |
| language | English |
| last_indexed | 2024-12-21T23:27:25Z |
| publishDate | 2014-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of King Saud University: Engineering Sciences |
| spelling | doaj.art-3e66f522d90e46d19c970fff398398682022-12-21T18:46:34ZengElsevierJournal of King Saud University: Engineering Sciences1018-36392014-01-01261698110.1016/j.jksues.2012.12.003Gravitation search algorithm: Application to the optimal IIR filter designSuman Kumar Saha0Rajib Kar1Durbadal Mandal2S.P. Ghoshal3Department of Electronics and Communication Engineering, National Institute of Technology, Durgapur, West Bengal, IndiaDepartment of Electronics and Communication Engineering, National Institute of Technology, Durgapur, West Bengal, IndiaDepartment of Electronics and Communication Engineering, National Institute of Technology, Durgapur, West Bengal, IndiaDepartment of Electrical Engineering, National Institute of Technology, Durgapur, West Bengal, IndiaThis paper presents a global heuristic search optimization technique known as Gravitation Search Algorithm (GSA) for the design of 8th order Infinite Impulse Response (IIR), low pass (LP), high pass (HP), band pass (BP) and band stop (BS) filters considering various non-linear characteristics of the filter design problems. This paper also adopts a novel fitness function in order to improve the stop band attenuation to a great extent. In GSA, law of gravity and mass interactions among different particles are adopted for handling the non-linear IIR filter design optimization problem. In this optimization technique, searcher agents are the collection of masses and interactions among them are governed by the Newtonian gravity and the laws of motion. The performances of the GSA based IIR filter designs have proven to be superior as compared to those obtained by real coded genetic algorithm (RGA) and standard Particle Swarm Optimization (PSO). Extensive simulation results affirm that the proposed approach using GSA outperforms over its counterparts not only in terms of quality output, i.e., sharpness at cut-off, smaller pass band ripple, higher stop band attenuation, but also the fastest convergence speed with assured stability.http://www.sciencedirect.com/science/article/pii/S1018363912000517IIR filterGSAEvolutionary optimization techniquesStability |
| spellingShingle | Suman Kumar Saha Rajib Kar Durbadal Mandal S.P. Ghoshal Gravitation search algorithm: Application to the optimal IIR filter design Journal of King Saud University: Engineering Sciences IIR filter GSA Evolutionary optimization techniques Stability |
| title | Gravitation search algorithm: Application to the optimal IIR filter design |
| title_full | Gravitation search algorithm: Application to the optimal IIR filter design |
| title_fullStr | Gravitation search algorithm: Application to the optimal IIR filter design |
| title_full_unstemmed | Gravitation search algorithm: Application to the optimal IIR filter design |
| title_short | Gravitation search algorithm: Application to the optimal IIR filter design |
| title_sort | gravitation search algorithm application to the optimal iir filter design |
| topic | IIR filter GSA Evolutionary optimization techniques Stability |
| url | http://www.sciencedirect.com/science/article/pii/S1018363912000517 |
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