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Toplam kayıt 7, listelenen: 1-7
Subspace-Based Spectrum Estimation By Nuclear Norm Minimization
(IEEE, 2013)
Subspace-based methods have been effectively used to estimate multi-input/multi-output, linear-time-invariant systems from noisy spectrum samples. In these methods, a critical step is splitting of two invariant subspaces ...
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 ...
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 ...
Road profile modeling by subspace identification methods
(Institute of Electrical and Electronics Engineers Inc., 2015)
In this paper, spectral models of road profiles using nonparametric and subspace identification methods are developed from road elevation measurements. First, power spectra of road profiles are estimated on uniform grids ...
Road Profile Modeling by Subspace Identification Methods
(IEEE, 2015)
In this paper, spectral models of road profiles using nonparametric and subspace identification methods are developed from road elevation measurements. First, power spectra of road profiles are estimated on uniform grids ...
Regularized Nuclear Norm Spectrum Estimation in Frequency Domain
(IEEE, 2013)
Subspace-based methods have been effectively used to estimate multi-input/multi-output, discrete-time, linear-time invariant systems from spectrum samples. A critical step in these methods is the splitting of causal and ...