Adaptive IIR identification of stochastic systems with noisy input-output data (Q2731050)
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scientific article; zbMATH DE number 1625469
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Adaptive IIR identification of stochastic systems with noisy input-output data |
scientific article; zbMATH DE number 1625469 |
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23 April 2002
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adaptive infinite impulse response identification
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linear discrete-time systems
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noise variances
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bias-eliminated least squares
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0.91648835
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0.9075426
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0.90687156
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0.88959885
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0.8895229
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0.88634217
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Adaptive IIR identification of stochastic systems with noisy input-output data (English)
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The paper is concerned with adaptive infinite impulse response (IIR) identification of linear discrete-time systems where both the output and the input are contaminated by zero-mean white measurement noise. By assumption, the noises are mutually independent. The aim is to identify the system parameters from the noisy input-output measurements. The proposed method is based on a numerically efficient procedure for estimating the measurement noise variances and then implementation of the bias-eliminated least squares to solve the estimation problem. The computational aspects and tracking ability of the method are illustrated by means of numerical examples.
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