IEEE Transactions on Automatic Control · 1995 · 76 citations · 13 references
EngineeringElectrical EngineeringMathematicsDynamical SystemsOptimizationUncertainty QuantificationFrequency ResponseFrequency-domain AnalysisParameter EstimationParameter Estimation Under UncertaintySystem IdentificationTransfer FunctionsLinear Time-invariant SystemsNumerical Stability AnalysisOrthogonal PolynomialsParametric Model IdentificationParametric System IdentificationTransfer Function EstimationTransfer Function IdentificationTransfer Function Models
It is shown that rational transfer function models based on orthogonal Forsythe polynomials minimize the condition number of the Jacobian of estimators in a least-squares framework. As a result, very high order linear time-invariant systems can be identified. The numerical stability of the estimation of the parameters and their derived quantities (zeros, poles, ...) are obtained. Statistical uncertainty bounds are provided. The method is illustrated on a 100th order simulated system and a 120th order measured beam-structure.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
13
Practical methods of optimization
Mathematics and Computers in Simulation · 1988 · 5.9K citations
Time Series: Data Analysis and Theory.
David R. Brillinger · Biometrics · 1981 · 795 citations
The Theory of Statistical Inference.
David R. Cox, S. Zacks · Biometrika · 1972 · 456 citations