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Gaussian mixture model for enhancing the quality of transmission estimation in optical networks: a machine learning approach. [PDF]

Sci Rep
Sahu S, Clement JC.
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Exploring neural manifolds across a wide range of intrinsic dimensions. [PDF]

PLoS Comput Biol
Fadanni J, Pacelli R, Zucchetta A, Rotondo P, Allegra M.   +4 more
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Adaptive Bayesian learning for stability characterization of re-entry vehicles. [PDF]

Sci Rep
Tiwari B, Musharrat L, Romeo SAS, Kassem A, Kara K, San O.   +5 more
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Simultaneous Nonlinear Estimation

Technometrics, 1966
An iterative procedure is given for the estimation of a vector of parameters some of which may be common to more than one of a set of nonlinear regression equations in the model presented. The procedure is given for the situation when the covariance matrix in the model is known and is extended to include the model when the covariance matrix is unknown.
Beauchamp, J. J., Cornell, R. G.
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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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Nonlinear Estimation

2019
Nonlinear Estimation: Methods and Applications with Deterministic Sample Points focusses on a comprehensive treatment of deterministic sample point filters (also called Gaussian filters) and their variants for nonlinear estimation problems, for which no closed-form solution is available in general.
Shovan Bhaumik, Paresh Date
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NICELY NONLINEAR ENGINE TORQUE ESTIMATOR

IFAC Proceedings Volumes, 2005
In automotive powertrain control strategy, engine torque estimators are preferred to expensive sensors for obvious economic reasons. In the literature several works have been presented proposing both instantaneous engine torque and mean engine torque estimators.
P. FALCONE, FIENGO G, L. GLIELMO
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Nonlinear Estimation and Asymptotic Approximations

Econometrica, 1978
central objective of this paper is to present a series expansion of nonlinear estimators in order to facilitate an analysis of the distributions of such estimators. Where the estimator under consideration is a maximum likelihood estimator, the method provides somewhat more information, as well as higher order approximations to the distributions of the ...
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