An extended alternating projection neural networks based weak-signal separation algorithm

Aiming at a kind of specific situation encountered in practice, the paper proposes a weak-signal separation algorithm based on extended alternating projection neural networks by combining the time-domain features of the signal with the frequency-domain features of the signal and taking advantage of...

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Bibliographic Details
Main Authors: Wang Jin-gen, Chen Shi-fu, Gong Shen-guang, Chen Zhao-qian
Format: Conference Proceeding
Language:English
Subjects:
Algorithm design and analysis
CADCAM
Computer aided manufacturing
Interference
Libraries
Neural networks
Signal processing
Signal processing algorithms
Software algorithms
Source separation
Online Access:Request full text
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Summary:Aiming at a kind of specific situation encountered in practice, the paper proposes a weak-signal separation algorithm based on extended alternating projection neural networks by combining the time-domain features of the signal with the frequency-domain features of the signal and taking advantage of conclusions on EAPNN. Simulation results demonstrate that the algorithm is effective and that the EAPNN-based signal separation algorithm is better than the RLS-based signal separation algorithm. Although the EAPNN-based algorithm is designed for the specific situation, it is also applicable to the other situations and a basic frame of the EAPNN-based signal separation is presented. Owing to adopting neural network structure, the EAPNN-based algorithm is prone to parallel computation and VLSI design, consequently can satisfy real-time processing needs.
DOI:10.1109/RISSP.2003.1285634