Particle swarm optimisation of a discontinuous control for a wheeled mobile robot with two trailers
International Journal of Computer Applications in Technology
Gaussian Cramer-Rao bound for direction estimation of noncircular signals in unknown noise fields
IEEE Transactions on Signal Processing
MUSIC-like estimation of direction of arrival for noncircular sources
IEEE Transactions on Signal Processing
Stochastic Crame´r-Rao bound for noncircular signals with application to DOA estimation
IEEE Transactions on Signal Processing
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
International Journal of Computing Science and Mathematics
Time-varying social emotional optimisation algorithm
International Journal of Computing Science and Mathematics
An improved particle swarm optimisation for solving generalised travelling salesman problem
International Journal of Computing Science and Mathematics
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In order to resolve complex continuous optimisation problem, a cultural quantum-inspired shuffled frog leaping CQSFL algorithm is proposed. The proposed CQSFL applies the quantum knowledge strategy and new quantum leaping equations to shuffled frog leaping algorithm, and thus has the advantages of low computational complexity and fast convergence. As a key step of CQSFL algorithm, leaping movement is modelled as guided cultural behaviour and thus may improve the capability of SFLA to find the optimal solution. Then we applied the proposed CQSFL algorithm in direction finding problem of non-circular signals, which is a hot spot in domain of communication. Then, based on CQSFL algorithm and non-circular maximum likelihood NML algorithm, a new direction finding method is proposed, which is called CQSFL-NML algorithm. Monte-Carlo simulations have proved that the CQSFL-NML method has good performance for non-coherent and coherent non-circular signals.