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Focusing on errors-in-variables (EIV) methods, this book delves into their role in system identification aimed at uncovering physical laws rather than predicting future behavior. It highlights the challenges of parameter identifiability in EIV problems and provides sufficient conditions for achieving it. The author discusses various modeling aspects, including noise characterization and extensions to multivariable and continuous-time systems. Unique solutions are presented that effectively handle noisy data, contrasting with traditional methods like total least squares.
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Errors-in-Variables Methods in System Identification, Torsten Söderström
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- 2018
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