Momentum Constant Modulus Blind Equalization Algorithm Based on Global Artificial Fish Swarm Optimization Algorithm

DOI

10.2991/iccmcee-15.2015.23How to use a DOI?

Keywords

Momentum constant blind equalization; Global artificial fish swarm algorithm; Convergence speed

Abstract

In order to overcome local convergence of constant modulus blind equalization algorithm (CMA), the momentum constant modulus blind equalization algorithm(MCMA) based on global artificial fish swarm optimization algorithm(GAFSA-MCMA) is proposed. In this proposed algorithm, on the basis of making full use of the global artificial fish swarm algorithm(AFSA) with the fast convergence and global search ability, the position vector of the artificial fish is optimized and the global optimal position vector is used as the initial optimal weight vector of the MCMA. Compared with the CMA and MCMA, the proposed algorithm has fastest convergence rate and minimum mean square error(MSE).

Copyright

© 2015, 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  - Chuan He
AU  - YeCai Guo
AU  - Hui Wang
AU  - LiHua Wang
PY  - 2015/11
DA  - 2015/11
TI  - Momentum Constant Modulus Blind Equalization Algorithm Based on Global Artificial Fish Swarm Optimization Algorithm
BT  - Proceedings of the 2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering
PB  - Atlantis Press
SP  - 111
EP  - 114
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccmcee-15.2015.23
DO  - 10.2991/iccmcee-15.2015.23
ID  - He2015/11
ER  -