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US 2019/0154779 A1Published application
System and methods for dynamic covariance estimation of a multivariate signal
OwnerMaziar Yaesoubi, Vince Calhouninventors
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Abstract
The invention is directed to a system and methods of capturing rapid changes in complex systems by examining the interaction of the various components within the system. This may be accomplished by decomposing a multivariate signal into a dictionary of elements and a corresponding sparse mixing matrix. Each dictionary element may provide a rank-1 estimation of a disjoint partition of time points of the signal that may permit estimation of the covariance of each partition using an outer-product of the corresponding dictionary element.
Claims7
A method for capturing dynamic covariance of a multivariate signal comprising the steps of:
- receiving an input multivariate signal;
- decomposing the input multivariate signal into a dictionary and a sparse mixing matrix, wherein the decomposing step further comprises the step of representing the input multivariate signal as a plurality of data points, wherein each data point is represented by a singleton dictionary element;
- and
- estimating the dynamic covariance of a partition of data-points using a self-outer product, wherein the self-outer product corresponds to the singleton dictionary element up to a scaling value.
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