Blind Separation of Process signals

Blind Separation of Process signals[J]. Journal of East China University of Science and Technology, 1999, (5): 510-513.

Citation:

Blind Separation of Process signals[J]. Journal of East China University of Science and Technology, 1999, (5): 510-513.

Citation:

Blind Separation of Process signals[J]. Journal of East China University of Science and Technology, 1999, (5): 510-513.

Abstract

With a sampling channel added, the noise mixed in process signals can be reduced by using the reduced HJ neural network (RHJNN) which is proposed in this paper based on signal blind separation. Results of computational simulations for different systems and signal combinations show RHJNN is effective, stable and robust.

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