Results 211 to 220 of about 118,549 (265)

On parametric density estimation

Biometrika, 1989
Let p(x,\(\vartheta)\) be the density of a random variable x. A random sample \(s_ n=(x_ 1,...,x_ n)\) of size n is available from the distribution. By y a future observation from this distribution is denoted. Two distinct methods of estimating p(y\(| \vartheta)\) are known. The estimative method uses \[ p(y| {\hat \vartheta}_ n)=p(y| \vartheta ={\hat \
El-Sayyad, G. M., Samiuddin, M., Al-Harbey, A. A.   +2 more
openaire   +2 more sources

Parametric Estimation of Cumulants

Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005., 2006
The problem of higher-order cumulants estimation is addressed in this paper. Higher-order cumulants are necessary in many applications, such as blind source separation (BSS) and blind deconvolution. In these applications, the cumulants are usually estimated using sample estimation.
Yair Noam, Joseph Tabrikian
openaire   +1 more source

Parametric estimation with a class of M-estimators

Mathematical Methods of Statistics, 2009
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +3 more sources

A parametric approach to bispectrum estimation

ICASSP '84. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
Higher order spectra provide information about processes not contained in the ordinary power spectrum such as the degree of nonlinearity and deviations from normality. The bispectrum which is a third order spectrum provides information about quadratic phase coupling among harmonic components.
Mysore R. Raghuveer, Chrysostomos L. Nikias   +1 more
openaire   +1 more source

Bispectrum estimation: A parametric approach

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1985
Higher order spectra contain information about random processes that is not contained in the ordinary power spectrum such as the degree of nonlinearity and deviations from normality. Estimation of the bispectrum, which is a third-order spectrum, has been applied in various fields to obtain information regarding quadratic phase coupling among harmonic ...
Raghuveer M. Rao, Chrysostomos L. Nikias
openaire   +1 more source

Non-parametric estimates of overlap

Statistics in Medicine, 2001
Kernel densities provide accurate non-parametric estimates of the overlapping coefficient or the proportion of similar responses (PSR) in two populations. Non-parametric estimates avoid strong assumptions on the shape of the populations, such as normality or equal variance, and possess sampling variation approaching that of parametric estimates.
R A, Stine, J F, Heyse
openaire   +2 more sources

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
openaire   +1 more source

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
openaire   +2 more sources

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
openaire   +1 more source