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Finally, FastICA in time domain is derived based on instantaneous BSS system, and convolutional mixture BSS algorithm in frequency domain is obtained based on convolutional mixture BSS in time domain. Then we combine the two algorithms together and present the complex-value FastICA algorithm in frequency domain, which is a new BSS technique. We merge preprocessing in time domain and correlation coefficient solution in time domain into this new algorithm and present Time-Frequency domain FastICA BSS System.

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The main job and contribution of this paper are as follows:Based on narrowband signal processing, we propose a new method for FH signal blind detection and blind parameter estimation. Firstly, compute the cross-correlation function of FH signals from multichannels, then we get the cross power spectral density matrixCSDM Secondly, select the hops of FH signals from the CSDM via processing and analyzing the CSDM, meanwhile reduce the influence coming from noise, fixed frequency signal and other interferences; Lastly, estimating the DOA of every hop and according to the DOA, we can separate the hops, get the number of FH signals and their parameters. Propose a new method for designing the threshold in FH signal detection. This method makes it easy to get the threshold by theoretic computing and it can extremely reduce the interference of non-FH signals.Based on broadband signal processing, we propose a new method for FH signal blind detection and blind parameter estimation. Firstly, get the DOA of the signals by wideband spatial spectrum estimation; secondly, separate the signals by spatial filtering using wideband beamformer; Lastly, we propose two methods for FH signal blind detection and blind parameter estimation, one is for several constant hop-rate FH signals whose dwell-time are different and another is for a single FH signal whose hop-rate is alterable.By employing spatial interpolation in broadband signal beamforming, it can reduce the number of antenna elements and corresponding RF modules, A/D converters, etc. It can also eliminate the mutual coupling between antenna elements while getting the narrower main beamwidth and lower sidelobe level.

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The contributions of this paper are followed:1 IntroductionIntroduce the concept "Blind" and present MEMO blind source separation model.2 Research on the instantaneous mixture systemReview the techniques developed for the demixing of the instantaneous mixture case.3 Research on the linear convolutive systemModel the linear convolutive system and review the deconvolution approaches in time domain.4 Introduce a new method to MIMO BSSA new approach to MIMO blind source separation in frequency domain is introduced, experimental tests are conducted,and results are satisfied.

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Then, the relation between vibration and sound, the acoustic holography method, the indeterminacy and identifiability of BSS, the BSS algorithm are discussed in detail. Based on above researches, the dissertation is divided in following four sections. The first section investigates the BSS algorithm suitable to acoustic feature separation. The algorithm of the joint approximate diagonalization of eigen-matrices is proposed. The spectra or the time-frequency distributions of source signals are the interesting features in ABD and they are separated from mixing signals by JADE algorithm. Then, the convolutive mixing model is transformed into a high-dimension instantaneous mixing model, and the deconvolution of source signals is achieved by the joint approximate block diagonalization of eigen-matrices. The proposed algorithm has a global minimum, and it is unsensitive to noise interference.

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