Adaptive digital filtering using the bio-inspired firefly algorithm

M. Hussain; William Kenneth Jenkins

doi:10.1109/ACSSC.2017.8335460

Adaptive digital filtering using the bio-inspired firefly algorithm

M. Hussain, William Kenneth Jenkins

College of Agricultural Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

13 Scopus citations

Abstract

The Lévy Flights variation of the bio-inspired Firefly Algorithm (LFFA) combines the Firefly Algorithm based on how fireflies interact through flashes and a random-step function based on the Lévy distribution. The LFFA, the Genetic Algorithm (GA), and the Particle Swarm Optimization Algorithm (PSOA) are compared when used for adaptive IIR system identification. Comparisons of the LFFA in direct, cascade, and parallel form structures suggest that 1) the LFFA is more effective than the GA and PSOA, 2) the LFFA adaptive algorithm works well for all structures that were experimentally tested, including a nonlinear Volterra structure, and 3) the LFFA appears to perform most effectively.

Original language	English (US)
Title of host publication	Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
Editors	Michael B. Matthews
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	816-819
Number of pages	4
ISBN (Electronic)	9781538618233
DOIs	https://doi.org/10.1109/ACSSC.2017.8335460
State	Published - Jul 2 2017
Event	51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017 - Pacific Grove, United States Duration: Oct 29 2017 → Nov 1 2017

Publication series

Name	Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
Volume	2017-October

Other

Other	51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017
Country/Territory	United States
City	Pacific Grove
Period	10/29/17 → 11/1/17

All Science Journal Classification (ASJC) codes

Control and Optimization
Computer Networks and Communications
Hardware and Architecture
Signal Processing
Biomedical Engineering
Instrumentation

Access to Document

10.1109/ACSSC.2017.8335460

Cite this

Hussain, M., & Jenkins, W. K. (2017). Adaptive digital filtering using the bio-inspired firefly algorithm. In M. B. Matthews (Ed.), Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017 (pp. 816-819). (Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017; Vol. 2017-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACSSC.2017.8335460

Hussain, M. ; Jenkins, William Kenneth. / Adaptive digital filtering using the bio-inspired firefly algorithm. Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. editor / Michael B. Matthews. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 816-819 (Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017).

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title = "Adaptive digital filtering using the bio-inspired firefly algorithm",

abstract = "The L{\'e}vy Flights variation of the bio-inspired Firefly Algorithm (LFFA) combines the Firefly Algorithm based on how fireflies interact through flashes and a random-step function based on the L{\'e}vy distribution. The LFFA, the Genetic Algorithm (GA), and the Particle Swarm Optimization Algorithm (PSOA) are compared when used for adaptive IIR system identification. Comparisons of the LFFA in direct, cascade, and parallel form structures suggest that 1) the LFFA is more effective than the GA and PSOA, 2) the LFFA adaptive algorithm works well for all structures that were experimentally tested, including a nonlinear Volterra structure, and 3) the LFFA appears to perform most effectively.",

author = "M. Hussain and Jenkins, {William Kenneth}",

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Hussain, M & Jenkins, WK 2017, Adaptive digital filtering using the bio-inspired firefly algorithm. in MB Matthews (ed.), Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017, vol. 2017-October, Institute of Electrical and Electronics Engineers Inc., pp. 816-819, 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017, Pacific Grove, United States, 10/29/17. https://doi.org/10.1109/ACSSC.2017.8335460

Adaptive digital filtering using the bio-inspired firefly algorithm. / Hussain, M.; Jenkins, William Kenneth.
Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. ed. / Michael B. Matthews. Institute of Electrical and Electronics Engineers Inc., 2017. p. 816-819 (Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017; Vol. 2017-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AB - The Lévy Flights variation of the bio-inspired Firefly Algorithm (LFFA) combines the Firefly Algorithm based on how fireflies interact through flashes and a random-step function based on the Lévy distribution. The LFFA, the Genetic Algorithm (GA), and the Particle Swarm Optimization Algorithm (PSOA) are compared when used for adaptive IIR system identification. Comparisons of the LFFA in direct, cascade, and parallel form structures suggest that 1) the LFFA is more effective than the GA and PSOA, 2) the LFFA adaptive algorithm works well for all structures that were experimentally tested, including a nonlinear Volterra structure, and 3) the LFFA appears to perform most effectively.

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Hussain M, Jenkins WK. Adaptive digital filtering using the bio-inspired firefly algorithm. In Matthews MB, editor, Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 816-819. (Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017). doi: 10.1109/ACSSC.2017.8335460

Adaptive digital filtering using the bio-inspired firefly algorithm

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