The Complex Blind Deflation Algorithm Based Particle Swarm Optimization with Survival of the Fittest Mechanism
- 10.2991/isccca.2013.101How to use a DOI?
- particle swarm optimization (PSO), complex signal, blind deflation, algorithm
For multi-constraint nonlinear optimization, this paper puts forward a complex blind deflation algorithm based particle swarm optimization with survival of the fittest mechanism(CBD-PSOSFM) which has faster convergence speed, and then gives a quantificational formula of the improved convergence speed, discusses implement method and the rule of parameters design; Because of the blind source separation (BSS) optimization characteristic in nature, the algorithm can be used to implement semi-BSS with nonlinear multi-constraint. For active object echo detection, the paper sets up fitness function with the multi-constraint like as kurtosis, energy and outline and forms the complex blind deflation algorithm. Finally, the simulation experiment of blind deflation to complex echo validates the algorithm’s validity and faster convergence capability
- © 2013, 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/).
Cite this article
TY - CONF AU - Wei Zhao AU - Chunpeng Dong PY - 2013/02 DA - 2013/02 TI - The Complex Blind Deflation Algorithm Based Particle Swarm Optimization with Survival of the Fittest Mechanism BT - Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation (ISCCCA 2013) PB - Atlantis Press SP - 411 EP - 414 SN - 1951-6851 UR - https://doi.org/10.2991/isccca.2013.101 DO - 10.2991/isccca.2013.101 ID - Zhao2013/02 ER -