A Conjugate Gradient Method and Simulated Annealing for Blind Separation of Sources
IWANN '01 Proceedings of the 6th International Work-Conference on Artificial and Natural Neural Networks: Bio-inspired Applications of Connectionism-Part II
Fast and robust fixed-point algorithms for independent component analysis
IEEE Transactions on Neural Networks
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This paper presents a novel block adaptive Independent Component Analysis (ICA) algorithm based on the conjugate gradient method. The algorithm is suitable for application in dynamic environments. Simulation results employing the proposed method for interference rejection in wireless receivers are given. It is shown that the new algorithm outperforms the Fast-ICA algorithm under dynamic conditions. Consequently, the proposed algorithm lends itself to practical applications in mobile cellular systems for higher user mobility, handoff, and rapid changing channel conditions.