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- W2358742143 abstract "The traditional feedforward neural network blind source separation algorithm is imperfect because of its fixed learning step.Although the self-adaptive step size algorithm based on Sigmoid-function can overcome the shortcomings of fixed step,its steady-state performance is poor.According to this problem,this paper proposed an improved self-adaptive step algorithm,which could flexibly control the shape of the step curve and the shape changed more slowly near the zeros than Sigmoid-function,the performance was more excellent.Secondly,considering the insufficient of feedforward neural network structure,this paper added a recursive structure into the whole model,adjusting learning step size with the improved self-adaptive step algorithm control algorithm.The simulation analysis shows that the algorithm has a faster separation speed and a better performance in convergence." @default.
- W2358742143 created "2016-06-24" @default.
- W2358742143 creator A5067937423 @default.
- W2358742143 date "2013-01-01" @default.
- W2358742143 modified "2023-09-24" @default.
- W2358742143 title "Improved self-adaptive mixing neural network algorithm for blind source separation" @default.
- W2358742143 hasPublicationYear "2013" @default.
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