Matrix rank minimization approach to signal recovery and nonlinear function estimation for nonlinear ARX model with input nonlinearity

Katsumi Konishi, Masashi Fujii, Katsuyuki Kunida, Shinsuke Uda, Shinya Kuroda

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    This paper deals with an input/output signal recovery problem for nonlinear multiple-input single-output autoregressive exogenous (ARX) models with input nonlinearity, which are used in data-driven systems biology. A matrix rank minimization approach is applied, and a new signal recovery algorithm for nonlinear ARX models is provided. The proposed algorithm recovers output signals and nonlinear-transformed input signals on a linear subspace using some assumptions about nonlinear functions and does not require the exact knowledge of nonlinear functions. Numerical examples using experimental data of signal transduction of cellular systems show the efficiency of the proposed algorithm.

    Original languageEnglish
    Title of host publication2017 Asian Control Conference, ASCC 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1428-1431
    Number of pages4
    ISBN (Electronic)9781509015733
    DOIs
    Publication statusPublished - Feb 7 2018
    Event2017 11th Asian Control Conference, ASCC 2017 - Gold Coast, Australia
    Duration: Dec 17 2017Dec 20 2017

    Publication series

    Name2017 Asian Control Conference, ASCC 2017
    Volume2018-January

    Other

    Other2017 11th Asian Control Conference, ASCC 2017
    Country/TerritoryAustralia
    CityGold Coast
    Period12/17/1712/20/17

    All Science Journal Classification (ASJC) codes

    • Control and Optimization

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