Title :
Blind Source Separation of Underwater Acoustic Signal by Use of Negentropy-Based Fast ICA Algorithm
Author :
Tu Shijie ; Chen Hang
Author_Institution :
Northwestern Polytech. Univ., Xi´an, China
Abstract :
Based on in-depth study of independent component analysis (ICA) method and signal independence measure algorithm based on negentropy, the author first conducts pretreatment of centering and whitening the mixed data of underwater acoustic signal, and then applies the negentropy-based fast ICA algorithm to the blind source separation of underwater acoustic signal and performs simulation experiment. The simulation result indicates that the negentropy-based fast ICA algorithm can effectively solve the blind source separation problems in the signal, this also shows that the method has certain universality and has extensive application prospect in the signal processing field.
Keywords :
acoustic signal processing; blind source separation; independent component analysis; blind source separation; independent component analysis method; negentropy-based fast ICA algorithm; signal independence measure algorithm; underwater acoustic signal processing; Correlation; Data mining; Entropy; Random variables; Signal processing; Signal processing algorithms; Vectors; Centering; Fast ICA; Negentropy; Whitening;
Conference_Titel :
Computational Intelligence & Communication Technology (CICT), 2015 IEEE International Conference on
Conference_Location :
Ghaziabad
Print_ISBN :
978-1-4799-6022-4
DOI :
10.1109/CICT.2015.115