A Fuzzy Gravitational Search Algorithm to Design Optimal IIR Filters

Danilo Pelusi, Raffaele Mascella and Luca Tallini
Additional contact information
Danilo Pelusi: Faculty of Communication Sciences, University of Teramo, 64100 Teramo, Italy
Raffaele Mascella: Faculty of Communication Sciences, University of Teramo, 64100 Teramo, Italy
Luca Tallini: Faculty of Communication Sciences, University of Teramo, 64100 Teramo, Italy

Energies, 2018, vol. 11, issue 4, 1-18

Abstract: The goodness of Infinite Impulse Response (IIR) digital filters design depends on pass band ripple, stop band ripple and transition band values. The main problem is defining a suitable error fitness function that depends on these parameters. This fitness function can be optimized by search algorithms such as evolutionary algorithms. This paper proposes an intelligent algorithm for the design of optimal 8th order IIR filters. The main contribution is the design of Fuzzy Inference Systems able to tune key parameters of a revisited version of the Gravitational Search Algorithm (GSA). In this way, a Fuzzy Gravitational Search Algorithm (FGSA) is designed. The optimization performances of FGSA are compared with those of Differential Evolution (DE) and GSA. The results show that FGSA is the algorithm that gives the best compromise between goodness, robustness and convergence rate for the design of 8th order IIR filters. Moreover, FGSA assures a good stability of the designed filters.

Keywords: optimization algorithms; IIR filters; gravitational search algorithm; fuzzy systems (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/11/4/736/pdf (application/pdf)
https://www.mdpi.com/1996-1073/11/4/736/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:11:y:2018:i:4:p:736-:d:137811

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().