Results 221 to 230 of about 118,102 (264)

Estimation and control with cubic nonlinearities

Journal of Optimization Theory and Applications, 1983
The nonlinearities in a dynamic system and its measurement equations are assumed to be cubic and small, i.e., all proportional to a single scalar small parameter \(\epsilon\). The optimal digital nonlinear feedback control law is carried through the first power of \(\epsilon\), taking into account the non-Gaussian character of the state conditional ...
Shefer, M., Breakwell, J. V.
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ESTIMATING NONLINEAR STRUCTURAL RELATIONSHIPS

Advances and Applications in Statistics, 2018
Summary: We consider the estimation of a general nonlinear structural relationship when the model is identifiable. In contrast to traditional approaches, the estimation method proposed does not require knowledge of the error variances provided that the model is identifiable.
Mak, T. K., Nebebe, F.
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Estimation of parameters in nonlinear problems

Numerical Algorithms, 1998
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N. Mansouri, Jean-Pierre Kernévez
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Error estimation in nonlinear optimization

Journal of Global Optimization, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
William W. Hager, Delphine Mico-Umutesi
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Asymmetry of estimators in nonlinear regression

Biometrika, 1987
The distributions of estimators \({\hat \vartheta}\) of the parameter \(\vartheta\) of intrinsically nonlinear regression functions f(x,\(\vartheta)\) are unknown but even with normally distributed errors they are known to be skew. A measure of asymmetry \(\lambda\) (i) of the distribution of the i-th component \({\hat \vartheta}\)(i) of \({\hat ...
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On a class of nonlinear estimation problems

IEEE Transactions on Information Theory, 1964
The 'noise-in-noise' problem is viewed as an estimation problem rather than a detection problem. Specifically, this is the problem of estimating the random scale parameter 'a' from observations x(t) , where x(t) = aS(t) + N(t) \mbox{0 \leq t \leq T \leq \infty} . Here, S(t) and N(t) are Gaussian processes with known covariances. The optimal mean-square
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Linear estimation with transformed measurement for nonlinear estimation

IEEE Transactions on Aerospace and Electronic Systems, 2016
The linear minimum mean-square error (LMMSE) estimation plays an important role in nonlinear estimation. It is the best of all estimators that are linear in the measurement. However, it may not perform well for a highly nonlinear problem. A generalized linear estimation framework, namely, linear in transform (LIT) estimation, is proposed in this work ...
Yu Liu 0013, X. Rong Li, Huimin Chen
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Commutator Estimate for Nonlinear Subdivision

2014
Nonlinear multiscale algorithms often involve nonlinear perturbations of linear coarse-to-fine prediction operators S (also called subdivision operators). In order to control these perturbations, estimates of the “commutator” SF − FS of S with a sufficiently smooth map F are needed.
Peter Oswald, Tatiana Shingel
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Nonlinear Extrapolation Estimates of π

Acta Mathematicae Applicatae Sinica, English Series
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Xu, Wen-qing, Wang, Sha-sha, Xu, Da-chuan   +2 more
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Nonlinear Estimation

Technometrics, 1992
Thomas D. Sandry, Gavin J. S. Ross
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