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

研究成果: 著書/レポートタイプへの貢献会議での発言

抜粋

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.

元の言語英語
ホスト出版物のタイトル2017 Asian Control Conference, ASCC 2017
出版者Institute of Electrical and Electronics Engineers Inc.
ページ1428-1431
ページ数4
ISBN(電子版)9781509015733
DOI
出版物ステータス出版済み - 2 7 2018
イベント2017 11th Asian Control Conference, ASCC 2017 - Gold Coast, オーストラリア
継続期間: 12 17 201712 20 2017

出版物シリーズ

名前2017 Asian Control Conference, ASCC 2017
2018-January

その他

その他2017 11th Asian Control Conference, ASCC 2017
オーストラリア
Gold Coast
期間12/17/1712/20/17

    フィンガープリント

All Science Journal Classification (ASJC) codes

  • Control and Optimization

これを引用

Konishi, K., Fujii, M., Kunida, K., Uda, S., & Kuroda, S. (2018). Matrix rank minimization approach to signal recovery and nonlinear function estimation for nonlinear ARX model with input nonlinearity. : 2017 Asian Control Conference, ASCC 2017 (pp. 1428-1431). (2017 Asian Control Conference, ASCC 2017; 巻数 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASCC.2017.8287382