Stochastic system transformation using generalized orthonormal basis functions with applications to continuous-time system identification
✍ Scribed by Yoshito Ohta
- Publisher
- Elsevier Science
- Year
- 2011
- Tongue
- English
- Weight
- 334 KB
- Volume
- 47
- Category
- Article
- ISSN
- 0005-1098
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✦ Synopsis
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 transformeddiscrete-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.