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Optimization algorithms, an effective tool for the design of digital filters; a review
- Source :
- Journal of Ambient Intelligence and Humanized Computing; 20240101, Issue: Preprints p1-17, 17p
- Publication Year :
- 2024
-
Abstract
- Nowadays, optimal and intelligent design approaches are vital in almost all areas of engineering. Scientists and engineers are attempting to make frameworks and models more proficient and intelligent. This paper deals with a detailed investigation on design of various digital filters using optimization algorithms. Generally digital filters are classified into two types which are FIR and IIR filters and are again classified into one dimensional, two dimensional and three dimensional filters for signal, image and video respectively. The design of a digital filter that satisfies all the required conditions perfectly is a challenging factor. So, apart from the conventional mathematical methods, optimization algorithms can be used to design optimal digital filters. IIR Filters are infinite impulse response filter; they have impulse response of infinite duration. FIR Filters are finite impulse response filters; they have impulse response of finite duration. In this paper we have discussed the design of various optimal digital filters based on various optimization algorithms, for processing of signal, image and video. The design of digital filters based on Evolutionary algorithms and swarm intelligence algorithms like Genetic Algorithm, Particle Swarm Optimization, Artificial Bee Colony Optimization, Cuckoo Search Algorithm, Differential Evolution, Gravitational Search, Harmony Search, Spiral Optimization, teaching–learning based optimization, wind driven optimization, hybridization of optimization algorithm are presented.
Details
- Language :
- English
- ISSN :
- 18685137 and 18685145
- Issue :
- Preprints
- Database :
- Supplemental Index
- Journal :
- Journal of Ambient Intelligence and Humanized Computing
- Publication Type :
- Periodical
- Accession number :
- ejs50927333
- Full Text :
- https://doi.org/10.1007/s12652-019-01431-x