Results 211 to 220 of about 10,692,124 (255)
Some of the next articles are maybe not open access.
2006
Abstract Parameter estimation is a common data analysis problem. Like Laplace, for example, we may be interested in knowing the mass of Saturn; or, like Millikan, the charge of the electron. In the simplest case, we are only concerned with the value of a single parameter; such elementary examples are the focus of this chapter. They serve
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Abstract Parameter estimation is a common data analysis problem. Like Laplace, for example, we may be interested in knowing the mass of Saturn; or, like Millikan, the charge of the electron. In the simplest case, we are only concerned with the value of a single parameter; such elementary examples are the focus of this chapter. They serve
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Adaptive Parameter Estimation and Control Design for Robot Manipulators With Finite-Time Convergence
IEEE transactions on industrial electronics (1982. Print), 2018For parameter identifications of robot systems, most existing works have focused on the estimation veracity, but few works of literature are concerned with the convergence speed.
Chenguang Yang +5 more
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Parameter Estimation for Nonlinear Functions Related to System Responses
International Journal of Control, Automation and Systems, 2023Ling Xu
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Residual analysis and parameter estimation of uncertain differential equations
Fuzzy Optimization and Decision Making, 2022Yang Liu, Baoding Liu
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2022
AbstractThe chapter provides a very short introduction to parameter estimation with least squares. It then introduces the method of maximum likelihood, focusing on its conceptual basis and use in hypothesis testing, and illustrates it with examples involving analytical and numerical methods.
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AbstractThe chapter provides a very short introduction to parameter estimation with least squares. It then introduces the method of maximum likelihood, focusing on its conceptual basis and use in hypothesis testing, and illustrates it with examples involving analytical and numerical methods.
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2006
Parameters are numbers which characterize random variables. They make possible the summarizing description of the observations, serve as the basis of statistical decisions and are calculated from the data. Point estimations and confidence estimations are introduced. Samples of the observed random variable are a starting point.
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Parameters are numbers which characterize random variables. They make possible the summarizing description of the observations, serve as the basis of statistical decisions and are calculated from the data. Point estimations and confidence estimations are introduced. Samples of the observed random variable are a starting point.
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Multiple emitter location and signal Parameter estimation
, 1986R. Schmidt
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Inverse problem theory - and methods for model parameter estimation
, 2004A. Tarantola
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A Recursive Parameter Estimation Algorithm for Modeling Signals with Multi-frequencies
Circuits Syst. Signal Process., 2020Ling Xu, Guanglei Song
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