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- W2615704622 abstract "This paper treats the problem of continuous-time model identification with unknown time delays from sampled data. The proposed method estimates the plant and the time delays in a separable way. More precisely, the plant is estimated by the standard recursive Least Square algorithm while the time delays are explicitly estimated by the Gauss-Newton algorithm. This means clear separation between the system dynamics and time delays. Numerical simulations are given at last to illustrate the validity of the proposed scheme." @default.
- W2615704622 created "2017-05-26" @default.
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- W2615704622 date "2016-12-01" @default.
- W2615704622 modified "2023-09-26" @default.
- W2615704622 title "Separable identification of continuous-time systems having multiple unknown time delays from sampled data" @default.
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- W2615704622 doi "https://doi.org/10.1109/ceit.2016.7929051" @default.
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