Proceedings of the 3rd International Conference on Mechatronics, Robotics and Automation

Signal Sparse Decomposition Based on Adaptive Chaos Fruit Fly Optimization Algorithm

Authors
Ming Yang, Wei Liu, Beichen Chen
Corresponding Author
Ming Yang
Available Online April 2015.
DOI
https://doi.org/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
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
3rd International Conference on Mechatronics, Robotics and Automation
Part of series
Advances in Computer Science Research
Publication Date
April 2015
ISBN
978-94-62520-76-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmra-15.2015.80How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

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  - 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  - https://doi.org/10.2991/icmra-15.2015.80
ID  - Yang2015/04
ER  -