## Abstract This paper presents two techniques, i.e. the proper orthogonal decomposition (POD) and the stochastic collocation method (SCM), for constructing surrogate models to accelerate the Bayesian inference approach for parameter estimation problems associated with partial differential equation
Fast GLS algorithm for parameter estimation
โ Scribed by M.S. Ahmed
- Publisher
- Elsevier Science
- Year
- 1984
- Tongue
- English
- Weight
- 491 KB
- Volume
- 20
- Category
- Article
- ISSN
- 0005-1098
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โฆ Synopsis
Akstraet--A computationally efficient off-line algorithm for estimating the parameters of a linear discrete-time SISO system is presented. The algorithm is based on the generalized leastsquares (GLS) principle. It is essentially a correlation version of the GLS method that (1) eliminates all the redundant computations, (2) does not require explicit evaluation of the residuals, (3) does not require explicit data filtering, and (4) eliminates the large storage requirement of the conventional offline GLS algorithm.
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