Signal Sparse Decomposition Based on Adaptive Chaos Fruit Fly Optimization Algorithm

DOI

10.2991/icmra-15.2015.80How to use a DOI?

Keywords

Sparse decomposition; Adaptive Chaos Fruit Fly Optimization Algorithm(ACFOA); Global optimum; Computational complexity

Abstract

Sparse decomposition can represent signal with small number of atoms. But, its high computation complexity hinders practical application. Fruit Fly Optimization Algorithm (FOA) improves the efficiency of atoms’ searching, but the solution sometimes is not global optimum. In order to solve this problem, Adaptive Chaos Fruit Fly Optimization Algorithm (ACFOA) is presented. In this paper, signal sparse decomposition based on ACFOA is presented. The experiment shows that the reconstructed signal is satisfied, and the computational complexity is reduced greatly

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  - Ming Yang
AU  - Wei Liu
AU  - Beichen Chen
PY  - 2015/04
DA  - 2015/04
TI  - Signal Sparse Decomposition Based on Adaptive Chaos Fruit Fly Optimization Algorithm
BT  - Proceedings of the 3rd International Conference on Mechatronics, Robotics and Automation
PB  - Atlantis Press
SP  - 405
EP  - 408
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmra-15.2015.80
DO  - 10.2991/icmra-15.2015.80
ID  - Yang2015/04
ER  -