Characterization of multiple time-varying transient sources from multivariate data sequences
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Characterization of multiple time-varying transient sources using sequential multivariate data is a broad and complex signal processing problem. In general, this process involves analyzing new observation vectors in a data stream of unknown length to determine if they contain the signatures of a source of interest (i.e., a signal), in which case the source's type and interference-free signatures may be estimated. This process may continue indefinitely to detect and classify several events of interest thereby yielding an aggregate description of the data's contents. Such capabilities are useful ...