Optimization IIR Filter Design Using Symbiotic Organism Search Algorithm

DOI

10.2991/msbda-19.2019.28How to use a DOI?

Keywords

Symbiotic organism search algorithm, IIR filter, Global optimization

Abstract

The possible multi-modal error surface is a challenge to the IIR filter design, which needs a flexible, easy to implement and stable global optimization algorithm to provide filter coefficient information. The Symbiotic Organism Search (SOS) algorithm is an effect global optimization algorithm which is proposed by Min-yuan Cheng in 2014. It simulates the symbiotic interaction between different populations in nature. In this paper, the IIR filter design in system recognition field based on the SOS algorithm will be described. Two IIR filters in different structures were used for experiment. The simulation results will be compared with some well-known algorithms that also provide solutions for IIR design. The comparative results show that: the design solution provided by the SOS algorithm is superior to Compared algorithms.

Copyright

© 2019, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Cao Han
AU  - Yongquan Zhou
PY  - 2019/08
DA  - 2019/08
TI  - Optimization IIR Filter Design Using Symbiotic Organism Search Algorithm
BT  - Proceedings of the 2019 International Conference on Modeling, Simulation and Big Data Analysis (MSBDA 2019)
PB  - Atlantis Press
SP  - 175
EP  - 180
SN  - 2352-538X
UR  - https://doi.org/10.2991/msbda-19.2019.28
DO  - 10.2991/msbda-19.2019.28
ID  - Han2019/08
ER  -