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Independent Component Analysis Enhancements For Source Separation In Immersive Audio Environments, Yue Zhao
Independent Component Analysis Enhancements For Source Separation In Immersive Audio Environments, Yue Zhao
Theses and Dissertations--Electrical and Computer Engineering
In immersive audio environments with distributed microphones, Independent Component Analysis (ICA) can be applied to uncover signals from a mixture of other signals and noise, such as in a cocktail party recording. ICA algorithms have been developed for instantaneous source mixtures and convolutional source mixtures. While ICA for instantaneous mixtures works when no delays exist between the signals in each mixture, distributed microphone recordings typically result various delays of the signals over the recorded channels. The convolutive ICA algorithm should account for delays; however, it requires many parameters to be set and often has stability issues. This thesis introduces the …