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- W2389969201 abstract "Aiming at the problems of slow convergence and low computational precision of existing blind source separation methods,a new blind source separation algorithm based on simulate anneal and particle swarm optimization is proposed.The proposed algorithm takes the negentropy of mixtures as a target function,which adaptively adjusts the inertia weight factor with changes of annealing temperature and fitness according to the state of the separation signal.It is almost as simple for implement as particle swarm optimization, but also can improve the abilities of seeking the global excellent result and evolution speed and stable performance.The experimental results demonstrate that the new algorithm has better performance than convolution blind source separation based-natural gradient and FastICA based-wavelet transform algorithm,and it could efficiently separate the mixture of real-time speech signal in real environment." @default.
- W2389969201 created "2016-06-24" @default.
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- W2389969201 date "2010-01-01" @default.
- W2389969201 modified "2023-09-23" @default.
- W2389969201 title "Real-time blind source separation for speech signal based on simulate anneal and particle swarm optimization" @default.
- W2389969201 hasPublicationYear "2010" @default.
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