![]() ![]() ![]() Under given assumptions, the separation technique will result in accurate partial sources. The proposed partial source separation technique is supported by several theorems. The partial source separation procedure has two main stages: obtain uncorrelated sources by eigenspace transformation and joint diagonalization and obtain partial periodic sources correlated with random noises from the uncorrelated sources by decorrelation. A partial unknown source separation technique is proposed by combining signal eigenspace transformation, covariance joint diagonalization and decorrelation of correlation sources. In this paper, a separation problem on partial unknown sources such as periodic sources correlated with random noises is introduced. Actual periodic disturbances are partial unknown sources in measured signals and have certain correlation with random noise sources in time domain. Separating and eliminating periodic disturbances from measured signals are a key problem to obtain original responses used for further system identification and evaluation. ![]()
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