Transient brain power supply positioning method and system based on non-negative block sparse Bayesian learning
A Bayesian learning and brain power location technology, applied in the field of EEG source tracing, can solve the problems of high false positives, non-negativity of unused signal power, influence of source location accuracy, etc., so as to improve the location effect and source location. effect of effect
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[0084] The present invention will be further described below with reference to the accompanying drawings and specific embodiments to better understand the invention and can be implemented, but the embodiments are not limited thereto.
[0085] The present invention is intended to learn based on non-negative blocks, and propose a transient brain power supply positioning method. The present invention first collects transient multi-channel EEG, calculating sample difference matrices, weighted the matrix per column, can be expressed as Laplace, and non-negative blocks on each brain section. The initial value of the iterative stop condition and the non-negative brain residential sparse support vector is set. Then, based on non-negative Gaussian distribution iteration updates the subtrision mean and covariance of the non-negative zone power vector and thus updated the non-negative partial power sparse support vector. Finally, the source positioning result is given by the latest non-negat...
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