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The problem of model identification in the presence of outliers has received great attention and a wide variety of outlier identification approaches have been proposed. Yet, there is a great need to seek for more general solutions and a unified framework to solving various practical problems. We propose to formulate the model identification problem under a robust unified framework consisting of consecutive...
In this paper, we present an improved algebraic geometry solution for the identification of switched ARX models in the presence of measurement noise. The procedure utilizes the highest order of sub-models, which is estimated by using statistical analysis of effective singular values in matrix rank determination. After embedding sub-models into a large continuous-time model for omitting the necessity...
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