Novel Crossover Genetic Artificial Fish Swarm DNA Encoding Sequence Based Blind Equalization Algorithm

DOI

10.2991/isci-15.2015.16How to use a DOI?

Keywords

Weighted multi-modulus blind equalization algorithm (WMMA); Artificial fish swarm algorithm (AFSA); novel crossover DNA genetic algorithm (ncDNA-GA)

Abstract

A novel crossover genetic artificial fish swarm DNA encoding sequence based weighted multi-modulus blind equalization algorithm(ncGAFS-DNA-WMMA) is proposed to solve the defect that error function doesn’t match with the signal constellation model in the multi-modulus blind equalization algorithm(MMA). The proposed algorithm can find the optimal DNA coding sequence through the novel crossover genetic artificial fish swarm algorithm with fast convergence and global searching ability. The initial optimal weight vector of the weighted MMA(WMMA) can obtained through decoding of the optimization DNA sequence. The simulation results show that the proposed algorithm has the faster convergence speed and smaller mean square error comparison with MMA, WMMA, and AFS-DNA-WMMA(weighted multi-modulus blind equalization algorithm based on DNA encoding sequences optimized by artificial fish swarm algorithm).

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  - 2015/01
DA  - 2015/01
TI  - Novel Crossover Genetic Artificial Fish Swarm DNA Encoding Sequence Based Blind Equalization Algorithm
BT  - Proceedings of the 2015 International Symposium on Computers & Informatics
PB  - Atlantis Press
SP  - 102
EP  - 109
SN  - 2352-538X
UR  - https://doi.org/10.2991/isci-15.2015.16
DO  - 10.2991/isci-15.2015.16
ID  - Wang2015/01
ER  -