Signal Separation Algorithm

Blind signal separation(BSS) is an interesting project in the field of signal processing.The technique of BSS can be applied in speech signal process-ing,image processing,communication processing,hydroacoustic signal process-ing,biomedical signal processing,data mining and many others.Because of wide usage of BSS,many researchers have devoted to the research of BSS.and the technique of BBS has been greatly improved.research on BSS has been going on for about twenty years. However,the problem of BSS has not been totally solved.All above stimulate us to be engaged in researches on BSS algorithm.The main parts of thesis are research on BSS theory and modification to BSS algorithm in difference practical field based on linear mix model.The main work and innovation are abstracted as follows.Since the algorithm of FastICA can't ensure the extraction of sources in order according to sources's character and fail with weak source,a blind signal extraction algorithm based on intelligent algorithm and Maximization of Non-gaussianity is proposed.AU simulation results show that the proposed algorithm show better performance to above problem than the algorithm of FastICA.Since S-ICA algorithm requires that sources are very sparse,which leads to bad performance sometimes.A new algorithm is presented by using the characteristic of SPARSE of the signals.It simplifies channel matrix and set up a new one. Based upon the independence among sources, the frequency spec-trums of the sources can be estimated from the observed signals in a new channel model.So that sources can be separated. Simulation studies are available to support the proposed algorithm.By research white operation how to effect on mix matrix,herein a new simpler and faster method based on higher order statistics is introduced in the 2 sources instance, which can estimate the separation matrix straightly. In more sources instance,only a few iterative operation should be required and there is no need to consider initial value.Good performance of simulations proves the prac-...