Study Of Blind Source Separation And Channel Coding Blind Recognition

Blind source/signal separation(BSS) has become a powerful tool in the areas ofsignal and image processing. The goal of BSS is to recover the original signals form aset of mixed signals with no or little a priori knowledge about the source and mixtures.There are many theories and algorithms results available, but which all have somelimitations in application.The main part of the thesis are reserch on BSS problem in complex communicationsignals, image signals and sppech signals of under-determined mode, for which theconditions are set much closer to the actual applications. The blind recognitiontechnology of channel coding has been increasingly important in the non-cooperativecommunication, thus the blind identification of RS codes is also mainly studied in thethesis, which improves the recognition performace and fills a gap to a certain extent.The thesis has made some achievements in the following aspects:(1)An improved natural gradient algorithm of over-determinded mode is proposedon the BSS of complex communication signalsBased on the elaborate introduction of ICA(Independent Component Analysis)theory and its extension, and related algorithms, by the simulation of the BSS ofcomplex communication signals, the reason of the natural gradient algorithm’sdivergence is analyzed. An improved natural gradient algorithm of over-determindedmode is proposed, which can separate the complex communication signals onover-determinded mode and the unknown or dynamic changing source number.(2)An improved fast fixed point algorithm is proposed on the BSS of image signalswith time structureStandard ICA algorithm is a complete failure when used on the BSS of the signalswith time structure, which are not statistical independent usually. An improved fastfixed point algorithm is proposed based on the classical AMUSE algorithm. The newalgorithm can achieve the BSS by using the nonstationarity of variance, and a newobjective function is given. the proposed algorithm can separate four channels of imigesignals compared to FastICA.(3) Based on the S-ICA(Sparse Independent Component Analysis), a newalgorithm is proposed on the BSS of speech signal on under-determined modeThe BSS problem on under-determined mode is more consistent with the actual situation and more challenging. Some improvements are made based on the two-stagealgorithm of S-ICA aftern the analyze of its defects. In the stage of source number andmixing matrix estimation, a new weighted potential function is deliverde. In the stage ofsource recovery, a method combined with MMSE(Minimum mean square error) isintroduced. The new algorithm can separate4channels of speech signals which arenonstationary.(4) A Fast blind recognition algorithm of RS codes by primitive element is proposedBased on the disvantages of available blind recognition of RS codes, A newalgorithm was presented to solve RS codes blind recognition problems. By searchingthe code length and the field parallelly based on the parith check function of primitiveelement, the recognition efficiency was improved. The reliability of roots’ searchingwas promoted by omitting error contained code words which did not accord with theprimitive element parith check. The generator polynomial was searched byforward-backward method using the continuity of roots to simplify calculations andaccelerate search speed. Simulation results indicate that new algorithm’s upper limit ofBER when correct recognition rate is90%has a significant increase.