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Creators/Authors contains: "Gugercin, Serkan"

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  1. ; ; (, SIAM Journal on Numerical Analysis)
    Free, publicly-accessible full text available April 30, 2026
  2. ; ; ; (, Computer Methods in Applied Mechanics and Engineering)
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  3. ; (, SIAM Journal on Numerical Analysis)
    Full Text Available 
  4. ; (, SIAM Journal on Scientific Computing)
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  5. ; ; (, Mechanical Systems and Signal Processing)
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  6. ; ; (, 2022 American Control Conference (ACC))
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  7. ; ; (, SIAM Journal on Scientific Computing)
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  8. ; (, Journal of Scientific Computing)
    Abstract We extend the Adaptive Antoulas-Anderson () algorithm to develop a data-driven modeling framework for linear systems with quadratic output (). Such systems are characterized by two transfer functions: one corresponding to the linear part of the output and another one to the quadratic part. We first establish the joint barycentric representations and the interpolation theory for the two transfer functions of systems. This analysis leads to the proposed algorithm. We show that by interpolating the transfer function values on a subset of samples together with imposing a least-squares minimization on the rest, we construct reliable data-driven models. Two numerical test cases illustrate the efficiency of the proposed method. 
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  9. ; (, 2021 American Control Conference (ACC))
    null (Ed.)
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  10. ; ; (, IFAC-PapersOnLine)
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