Modeling continuous-time processes via input-to-state filters
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Publication:856521
DOI10.1016/j.automatica.2006.02.014zbMath1115.93090OpenAlexW2158420882MaRDI QIDQ856521
Publication date: 7 December 2006
Published in: Automatica (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/1959.13/26054
Filtering in stochastic control theory (93E11) System identification (93B30) Stochastic systems in control theory (general) (93E03)
Related Items
Modeling continuous-time processes via input-to-state filters ⋮ On the indirect approaches for CARMA model identification ⋮ Some computational aspects of Gaussian CARMA modelling
Cites Work
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- The effects of rapid sampling in system identification
- On covariance function tests used in system identification
- Modeling continuous-time processes via input-to-state filters
- Adaptive computed torque control for rigid link manipulations
- Fast projection methods for minimal design problems in linear system theory
- Identification of continuous-time AR processes from unevenly sampled data
- Discrete-time stochastic systems. Estimation and control.
- Sampling in digital signal processing and control
- Performance evaluation of methods for identifying continuous-time autoregressive processes
- Estimation of continuous-time AR process parameters from discrete-time data
- Continuous-time AR process parameter estimation in presence of additive white noise
- MA estimation in polynomial time
- Vector ARMA estimation: a reliable subspace approach
- Computing stochastic continuous-time models from ARMA models
- On the expectation of the product of four matrix-valued Gaussian random variables
- The interpolation problem with a degree constraint
- Spectral estimation via selective harmonic amplification
- A generalized entropy criterion for Nevanlinna-Pick interpolation with degree constraint
- Spectral analysis based on the state covariance: the maximum entropy spectrum and linear fractional parametrization
- The structure of state covariances and its relation to the power spectrum of the input