Results 341 to 350 of about 2,762,871 (394)

Parametric Estimation in Hamiltonian Systems

2018 15th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), 2018
Here we present two numerical procedures for the identification of Hamiltonian systems, applying the Lagragian and Hamiltonian formalism. The property of First Integrals and their characteristics are used to treats the identification as stabilization. The derivative of first integrals is realized by a super-twist differentiator. The convergence of this
Alejandra Hernandez, Alexander S. Poznyak   +1 more
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Parametric estimation for normal mixtures

Pattern Recognition Letters, 1985
Described here are two approaches for estimating the parameters (a-priori probabilities, means, and covariances) of a mixture of normal distributions, given a finite sample X drawn from the mixture. One approach is based on a modification of the EM algorithm for computing maximum-likelihood estimates, while the other makes use of the fuzzy c- means ...
James C. Bezdek, Richard J. Hathaway, Vicki J. Huggins   +2 more
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Optimized parametric bispectrum estimation

ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing, 2003
When analyzing various signals produced by some nonlinear process, higher-order spectra are necessary to characterize the nonlinearity. For example, the bispectrum is very useful in analyzing three-wave nonlinear interaction data. An optimized parametric bispectrum estimation method is presented.
Chong Koo An, Sung Bae Kim, Edward J. Powers   +2 more
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Robust estimation with parametric score function estimation

IEEE International Conference on Acoustics Speech and Signal Processing, 2002
Robust estimation of signal parameters in the additive noise model has become an important problem. Its relevance can be attributed to the realisation that impulsive noise is present in communications channels. The approach to robust estimation taken here follows the M-estimation concept of robust statistics, except the score function is modeled as a ...
Ramon F. Brcich, Abdelhak M. Zoubir
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On the Estimation of Parametric Density Functions

Biometrika, 1980
SUMMARY The best invariant estimate of the parametric density function in statistical models invariant under a transformation group is derived. The estimate is best with respect to a goodness-of-fit criterion based on an informa,tion measure. We are concerned with the estimation of a parametric density function p(y I 0) using data x.
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On Information Inequalities in the Parametric Estimation

Theory of Probability & Its Applications, 1993
Let \(X_ 1,X_ 2,\dots\) be independent, identically distributed random variables, \(X_ i \in ({\mathcal X},\mu)\). Assume that \(X_ 1\) belongs to a distribution \(P_ \theta\) from a parametric family \(\{P_ t\); \(t \in \Theta\}\), where \(\Theta\) is an open subset of \(\mathbb{R}^ d\) and, for any \(t \in \Theta\), \(P_ t\) is absolutely continuous ...
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A parametric technique for time delay estimation

ICASSP '82. IEEE International Conference on Acoustics, Speech, and Signal Processing, 1984
Estimating the time-delay between two received signals is formulated as a parameter estimation problem for a certain spectral model. The model parameters are computed by a two step procedure: The modified Yule-Walker equations are used to estimate the autoregressive coefficients of the source signal, and a frequency domain squared error criterion is ...
Benjamin Friedlander, Boaz Porat
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On Coherence in Parametric Density Estimation

Biometrika, 1990
SUMMARY In parametric density estimation the existence of a prior distribution on the parameter dictates the use of the corresponding predictive density function as estimate. This paper argues that in a decision theory approach to parameter density estimation any loss function introduced should lead to this predictive result for situations where prior ...
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Parametric and Nonparametric FDR Estimation Revisited

Biometrics, 2006
Summary Nonparametric and parametric approaches have been proposed to estimate false discovery rate under the independent hypothesis testing assumption. The parametric approach has been shown to have better performance than the nonparametric approaches. In this article, we study the nonparametric approaches and quantify the underlying relations between
Wu, Baolin, Guan, Zhong, Zhao, Hongyu
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New SOC estimation method under multi-temperature conditions based on parametric-estimation OCV

Journal of Power Electronics (JPE), 2020
Qiuting Wang, Wei Qi
semanticscholar   +1 more source