Real-time identification of time-varying systems by non-parametric algorithms based on Parzen kernels

DOI10.1080/00207728508926737zbMath0577.93066OpenAlexW2077444112MaRDI QIDQ3699588

Leszek Rutkowski

Publication date: 1985

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207728508926737

zbMATH Keywords

non-stationary systemsreal-time identificationnon-parametric algorithmsParzen kernel techniques

Mathematics Subject Classification ID

Related Items (2)

On the Cesàro-Means-Based Orthogonal Series Approach to Learning Time-Varying Regression Functions ⋮ Nonparametric regression for nonstationary processes

Cites Work

• Nonparametric system identification by kernel methods
• Nonparametric algorithm for input signals identification in static distributed-parameter systems
• On system identification by nonparametric function fitting
• Nonparametric Identification for Diffusion Processes
• Asymptotically optimal discriminant functions for pattern classification
• On Estimation of a Probability Density Function and Mode

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