2004 International Symposium on Parallel Architectures, Algorithms and Networks (ISPAN'04) Particle Swarm Optimization Algorithm in Signal Detection and Blind Extraction Hong Kong, SAR, China May 10-May 12 ISBN: 0-7695-2135-5
Particle swarm optimization (PSO) algorithm, originated as a simulation of a simplified social system, is an evolutionary computation technique developed successfully in recent years. In this paper the binary and real-valued versions of PSO algorithm are exploited in two important signal processing paradigm: multiuser detection (MUD) and blind extraction of sources (BES), respectively. The novel approaches are effective and efficient with parallel processing structure and relatively feasible implementation. Simulation results validate either PSO-MUD or PSO-BES has a significant performance improvement over conventional methods.
Citation:
Ying Zhao, Junli Zheng, "Particle Swarm Optimization Algorithm in Signal Detection and Blind Extraction," ispan, pp.37, 2004 International Symposium on Parallel Architectures, Algorithms and Networks (ISPAN'04), 2004 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||