A Blind Equalization Algorithm Based on Global Artificial Fish Swarm and Genetic Optimization DNA Encoding Sequences

DOI

10.2991/iiicec-15.2015.31How to use a DOI?

Keywords

Stochastic conjugate gradient multi-modulus algorithm (SMMA); Global artificial fish swarm algorithm (GAFSA); DNA genetic algorithm (DNA-GA)

Abstract

A stochastic conjugate gradient multi-modulus algorithm based on global artificial fish swarm and genetic optimization DNA encoding sequences(GAFS-GDNA- SMMA) is proposed to solve the high computational loads, low convergence rate, and large mean square error(MSE) of the multi-modulus blind equalization algorithm(MMA). In this proposed algorithm, the optimal DNA coding sequence can be found and used as the initial optimal weight vector of the stochastic conjugate gradient MMA(SMMA) after decoding the optimization DNA sequences. The simulation results show that the proposed algorithm has the faster convergence speed and smaller mean square error comparison with MMA, SMMA, GA-DNA-SMMA(Genetic algorithm and DNA optimization based SMMA)

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  - Hui Wang
AU  - Yecai Guo
PY  - 2015/03
DA  - 2015/03
TI  - A Blind Equalization Algorithm Based on Global Artificial Fish Swarm and Genetic Optimization DNA Encoding Sequences
BT  - Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference
PB  - Atlantis Press
SP  - 131
EP  - 134
SN  - 2352-538X
UR  - https://doi.org/10.2991/iiicec-15.2015.31
DO  - 10.2991/iiicec-15.2015.31
ID  - Wang2015/03
ER  -