This paper presents a variant of the Recursive Gauss-Newton algorithm for identification of the model To derive the algorithm the formulae for the predictor and its derivatives have been transformed and then applied to build up more exact schema for the evaluation of the gradient and the Hessian. T
Recursive prediction error algorithms without a stability test
โ Scribed by Haim Weiss; John B. Moore
- Publisher
- Elsevier Science
- Year
- 1980
- Tongue
- English
- Weight
- 507 KB
- Volume
- 16
- Category
- Article
- ISSN
- 0005-1098
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โฆ Synopsis
In this paper, recursive prediction error identification schemes are studied which incorporate Kalman gain calculations to ensure exponential stability of the predictor and related recursions. Thus there is an alternative to the trial and error projection techniques and stability test calculations of earlier schemes with no compromise on convergence rate or computational effort. The resulting algorithms are then attractive for a wide range of applications.
๐ SIMILAR VOLUMES
A general recursive identification algorithm is found to have the same convergence properties as a family of off-line prediction error methods.
In this paper we present an alternative approach to the direct design of 1-D recursive digitalfilters satisfying prescribed magnitude specifications with or without constant group delay characteristic. This method uses an iterative method to calculate the coejkients of the$lter's transfer,function a