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Toplam kayıt 6, listelenen: 1-6
Spectrum estimation in innovation models by a nuclear norm optimization based algorithm
(IEEE, 2017)
In this paper, identification of multi-input/multioutput (Ml MO) state-space models in the innovation form by a regularized-nuclear norm optimization based subspace algorithm is studied. Parametrization issues arc carefully ...
Power Spectrum Estimation in Innovation Models by Nuclear Norm Optimization
(IEEE Computer Society, 2018)
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 ...
Spectrum estimation in frequency-domain by subspace and regularization-based algorithms: A survey
(IEEE, 2015)
In this survey article, we study methods to identify multi-input/multi-output, discrete-time, linear time-invariant systems from power spectrum measurements. First, we examine subspace-based identification algorithms. A ...
Time-domain identification of rational spectra with missing data
(IEEE, 2016)
In this paper, we study modelling of rational spectra from time-domain measurements when the measurement information is not complete. We propose a three-stage estimation scheme. In the first-stage, rational spectra are ...
Induction Motor Identification from Acoustic Noise Spectrum by a Covariance Subspace Algorithm
(IEEE Computer Society, 2018)
In this paper, we study identification of induction motors by using a recently developed covariance-based subspace algorithm from sound measurements. The sound data are collected by an array of five-microphones placed ...
Instrumental variable frequency-domain subspace identification
(2010)
In this paper, we study instrumental variable subspace identification of multi-input/multi-output linear-time-invariant, discrete-time systems from non-uniformly spaced frequency response measurements. A particular algorithm, ...