Statistical results for system identification based on quantized observations

DOI10.1016/j.automatica.2009.09.014zbMath1192.93120OpenAlexW2075554752MaRDI QIDQ976217

Fredrik Gustafsson, Rickard Karlsson

Publication date: 17 June 2010

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-52878

zbMATH Keywords

system identificationestimationquantization

Mathematics Subject Classification ID

Estimation and detection in stochastic control theory (93E10) Identification in stochastic control theory (93E12)

Related Items (10)

Granger causality from quantized measurements ⋮ Robust and nonlinear control literature survey (No. 17) ⋮ Approximation of optimal filter for Ornstein–Uhlenbeck process with quantised discrete-time observation ⋮ Closed-Loop System Identification Using Quantized Observations and Integrated Bispectra ⋮ Asymptotically efficient identification of FIR systems with quantized observations and general quantized inputs ⋮ On identification of FIR systems having quantized output data ⋮ Robust distributed maximum likelihood estimation with dependent quantized data ⋮ Convergence analysis of an online approach to parameter estimation problems based on binary observations ⋮ Identification of sparse FIR systems using a general quantisation scheme ⋮ Parameter estimation in systems with binary-valued observations and structural uncertainties

Cites Work

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• Asymptotically efficient parameter estimation using quantized output observations
• Effects of sampling and quantization on single-tone frequency estimation
• A necessary and sufficient condition for quantization errors to be uniform and white
• System identification using binary sensors

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