Generalized least squares innovation representation
โ Scribed by I. Bencsik; Gy. Michaletzky
- Publisher
- Elsevier Science
- Year
- 1988
- Tongue
- English
- Weight
- 414 KB
- Volume
- 11
- Category
- Article
- ISSN
- 0895-7177
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โฆ Synopsis
In this paper we shouldlike to give a unified approach to the stochastic realization problem of finite dimensional discrete time stochastic systems . The generalized least squares innovation representation /GLS IR/ developed in the paper has diagonal error covariance matrix in tie state space and orthonormed innovation process.Algorithm is presented for the identification of the parameters of the GLS IR.
๐ SIMILAR VOLUMES
A model for least-squares fitting of fuzzy-valued data is described. A previous process obtained for triangular fuzzy numbers is generalized and improved to include all fuzzy numbers represented by single maxima piecewise continuous functions with compact support. The new model is compared with the