ArticleScientific reports2025
Robust recursive estimation for the errors-in-variables nonlinear systems with impulsive noise.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The non-Gaussian characteristic of the external disturbance poses a great challenge for system modeling and identification. This paper develops a robust recursive estimation algorithm for the errors-in-variables nonlinear system with the impulsive noise. The algorithm is formulated by minimizing the continuous logarithmic mixed p-norm criterion, and is capable of giving a robust estimation against the impulsive noise through an adjustable weight gain. The nonlinear monomials of the noisy input are estimated by the recursive expressions based on the bias correction. Furthermore, a continuous logarithmic mixed p-norm based robust hierarchical estimation algorithm is derived to reduce the computational loads. The simulation studies demonstrate the feasibility of the proposed algorithms.
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