Iterative algorithms for the input and state recovery from the approximate inverse of strictly proper multivariable systems
Sign Up to like & getrecommendations! Published in 2018 at "Mechanical Systems and Signal Processing"
DOI: 10.1016/j.ymssp.2017.08.026
Abstract: Abstract This paper proposes new iterative algorithms for the unknown input and state recovery from the system outputs using an approximate inverse of the strictly proper linear time-invariant (LTI) multivariable system. One of the unique… read more here.
Keywords: state; approximate inverse; iterative algorithms; state recovery ... See more keywords
Sparse State Recovery Versus Generalized Maximum-Likelihood Estimator of a Power System
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DOI: 10.1109/tpwrs.2017.2715561
Abstract: This letter shows that the sparse state recovery optimization method is equivalent to the well-known Huber M-estimator, and then justifies its robustness to bad data. We derive the total influence functions of the Huber M-estimator… read more here.
Keywords: estimator; maximum likelihood; generalized maximum; sparse state ... See more keywords