Convex relaxations for robust identification of Wiener systems and applications

Burak Yilmaz, Mustafa Ayazoglu, Mario Sznaier, Constantino Manuel Lagoa

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

    6 Citations (Scopus)

    Abstract

    This paper considers the identification of Wiener systems in a worst case framework. Given some a priori information about the admissible set of plants, nonlinearities and measurement noise, and a posteriori experimental data, our goal is twofold: (i) establish whether the a priori and a posteriori information are consistent, and (ii) in that case find a model that interpolates the available experimental information within the noise level. As recently shown, this problem is generically NP hard both in the number of data points and the number of inputs to the non-linearity. Our main result shows that a computationally attractive relaxation can be obtained by recasting the problem as a rank-constrained semi-definite optimization and using existing tools specifically tailored to this type of problems. These results are illustrated with a practical application drawn from computer vision

    Original languageEnglish (US)
    Title of host publication2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
    Pages2812-2818
    Number of pages7
    DOIs
    StatePublished - Dec 1 2011
    Event2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011 - Orlando, FL, United States
    Duration: Dec 12 2011Dec 15 2011

    Other

    Other2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011
    CountryUnited States
    CityOrlando, FL
    Period12/12/1112/15/11

    Fingerprint

    Convex Relaxation
    Computer vision
    Semidefinite Optimization
    Nonlinearity
    Admissible Set
    Constrained Optimization
    Computer Vision
    NP-complete problem
    Interpolate
    Experimental Data
    Model

    All Science Journal Classification (ASJC) codes

    • Control and Systems Engineering
    • Modeling and Simulation
    • Control and Optimization

    Cite this

    Yilmaz, B., Ayazoglu, M., Sznaier, M., & Lagoa, C. M. (2011). Convex relaxations for robust identification of Wiener systems and applications. In 2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011 (pp. 2812-2818). [6161114] https://doi.org/10.1109/CDC.2011.6161114
    Yilmaz, Burak ; Ayazoglu, Mustafa ; Sznaier, Mario ; Lagoa, Constantino Manuel. / Convex relaxations for robust identification of Wiener systems and applications. 2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011. 2011. pp. 2812-2818
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    Yilmaz, B, Ayazoglu, M, Sznaier, M & Lagoa, CM 2011, Convex relaxations for robust identification of Wiener systems and applications. in 2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011., 6161114, pp. 2812-2818, 2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011, Orlando, FL, United States, 12/12/11. https://doi.org/10.1109/CDC.2011.6161114

    Convex relaxations for robust identification of Wiener systems and applications. / Yilmaz, Burak; Ayazoglu, Mustafa; Sznaier, Mario; Lagoa, Constantino Manuel.

    2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011. 2011. p. 2812-2818 6161114.

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

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    Yilmaz B, Ayazoglu M, Sznaier M, Lagoa CM. Convex relaxations for robust identification of Wiener systems and applications. In 2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011. 2011. p. 2812-2818. 6161114 https://doi.org/10.1109/CDC.2011.6161114