Real and complex analysis, 3rd ed.
Real and complex analysis, 3rd ed.
Automatica (Journal of IFAC) - Special issue on statistical signal processing and control
N4SID: subspace algorithms for the identification of combined deterministic-stochastic systems
Automatica (Journal of IFAC) - Special issue on statistical signal processing and control
A unifying theorem for three subspace system identification algorithms
Automatica (Journal of IFAC) - Special issue on trends in system identification
Orthonormal Basis Functions in Time and Frequency Domain: Hambo Transform Theory
SIAM Journal on Control and Optimization
Stochastic theory of continuous-time state-space identification
IEEE Transactions on Signal Processing
Subspace identification for continuous-time stochastic systems via distribution-based approach
Automatica (Journal of IFAC)
Minimal partial realization from generalized orthonormal basis function expansions
Automatica (Journal of IFAC)
| Hi-index | 22.15 |
This paper studies the system transformation using generalized orthonormal basis functions that include the Laguerre basis as a special case. The transformation of the deterministic systems is studied in the literature, which is called the Hambo transform. The aim of the paper is to develop a transformation theory for stochastic systems. The paper establishes the equivalence of continuous and transformed-discrete-time stochastic systems in terms of solutions. The method is applied to the continuous-time system identification problem. It is shown that using the transformed signals the PO-MOESP subspace identification algorithm yields consistent estimates for system matrices. An example is included to illustrate the efficacy of the proposed identification method, and to make a comparison with the method using the Laguerre filter.