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• W2912032500 abstract "Abstract Numerical procedures for dynamic system identification are discussed. Efficient algorithms for static least-squares problems provide a starting point for dynamic systems nonlinear programming methods. This paper shows that in dynamic systems, the additional computation time required for the first and the second gradients over function evaluation is small compared to static systems. This makes gradient procedures very attractive for dynamic system parameter estimation. Additional simplifications are made for linear systems. Finally, some practical simplifications are suggested to enable identification in large scale systems using current computers." @default.
• W2912032500 created "2019-02-21" @default.
• W2912032500 creator A5059717218 @default.
• W2912032500 date "1980-01-01" @default.
• W2912032500 modified "2023-10-15" @default.
• W2912032500 title "NONLINEAR PROGRAMMING FOR SYSTEM IDENTIFICATION" @default.
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• W2912032500 doi "https://doi.org/10.1016/b978-0-08-024491-4.50010-3" @default.
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