Power Spectrum Estimation in Innovation Models by Nuclear Norm Optimization

In this paper, identification of discrete-time power spectra of multi-input/multi-output models in innovation form from output-only time-domain measurements is studied. Two regularized nuclear norm minimization-based subspace algorithms are proposed. One of the algorithms is capable of handling missing data.

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