All

What are you looking for?

All
Projects
Results
Organizations

Quick search

  • Projects supported by TA ČR
  • Excellent projects
  • Projects with the highest public support
  • Current projects

Smart search

  • That is how I find a specific +word
  • That is how I leave the -word out of the results
  • “That is how I can find the whole phrase”

Regularized estimation with variable exponential forgetting

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26620%2F20%3APU138218" target="_blank" >RIV/00216305:26620/20:PU138218 - isvavai.cz</a>

  • Result on the web

    <a href="https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9304385" target="_blank" >https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9304385</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/CDC42340.2020.9304385" target="_blank" >10.1109/CDC42340.2020.9304385</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Regularized estimation with variable exponential forgetting

  • Original language description

    The real-time estimation of normal regression-type models with unknown time-varying parameters is considered and discussed from the Bayesian perspective. A novel tracking technique combining the variable regularization approach with the forgetting operation is derived and elaborated into algorithmic details. The regularization of the parameter covariance is accomplished by incorporating soft equality constraints on the regression parameters into the learning procedure. The resultant procedure is designed to smooth the parameter estimate, preventing it from changing too rapidly. Moreover, the form of the constraints guarantees a minimal amount of information about the parameter estimate, which makes the estimator robust with respect to poor system excitation. The forgetting of obsolete information is provided in two different parameterization options and is performed automatically in a way that complies with the degree of the process nonstationarity. The whole concept preserves the selfreproducibility of the statistics of the normal-Wishart distribution.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20205 - Automation and control systems

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    59th Conference on Decision and Control

  • ISBN

    978-1-7281-7446-4

  • ISSN

  • e-ISSN

  • Number of pages

    7

  • Pages from-to

    312-318

  • Publisher name

    IEEE

  • Place of publication

    New York

  • Event location

    Jeju Island, Republic of Korea

  • Event date

    Dec 14, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000717663400040