Zobrazeno 1 - 10
of 98
pro vyhledávání: '"G. Demoment"'
Autor:
Ali Mohammad-Djafari, G. Demoment
The Twelfth International Workshop on Maximum Entropy and Bayesian Methods in Sciences and Engineering (MaxEnt 92) was held in Paris, France, at the Centre National de la Recherche Scientifique (CNRS), July 19-24, 1992. It is important to note that,
Publikováno v:
International Journal of Mass Spectrometry. 215:175-193
This paper is a synthetic overview of regularization, maximum entropy and probabilistic methods for some inverse problems such as deconvolution and Fourier synthesis problems which arise in mass spectrometry. First we present a unified description of
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b72932f664863017c540bcdd2741c34b
https://doi.org/10.1016/s1387-3806(01)00562-0
https://doi.org/10.1016/s1387-3806(01)00562-0
Autor:
G. Demoment
Publikováno v:
Journal de Physique IV (Proceedings). 12:3-34
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0f64ae22917c4388a6d919f513d89ffa
https://doi.org/10.1051/jp42002001
https://doi.org/10.1051/jp42002001
Publikováno v:
IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control. 43:220-233
We address the problem of smooth power spectral density estimation of zero-mean stationary Gaussian processes when only a short observation set is available for analysis. The spectra are described by a long autoregressive model whose coefficients are
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f63fd0a31b8e85079e74ef0307098ef0
https://doi.org/10.1109/58.485948
https://doi.org/10.1109/58.485948
Autor:
G. Demoment, A. Herment
Publikováno v:
Le Journal de Physique Colloques. 51:C2-753
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6e36d58df365dc439bc3977f5d265a90
https://doi.org/10.1051/jphyscol:19902175
https://doi.org/10.1051/jphyscol:19902175
Publikováno v:
ICASSP
Restoration of an image distorted by a linear shift-invariant system is a 2-D deconvolution problem which is treated here in a Bayesian framework to stabilize the solution. The usual introduction of dynamics into the state equation to reduce the prob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1bb265dc8d775f292849ba4d4f36f213
https://doi.org/10.1109/icassp.1986.1169273
https://doi.org/10.1109/icassp.1986.1169273
Publikováno v:
ICASSP
Restoration of an image distorted by a linear spatially invariant system can be viewed as a 2-D deconvolution problem. The major difficulties lie in stabilizing the solution of such an ill-posed problem and in the computational burden inherent to the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::82d69af08766612f782a4e7dacc7ea70
https://doi.org/10.1109/icassp.1984.1172775
https://doi.org/10.1109/icassp.1984.1172775
Autor:
A. Houacine, G. Demoment
Publikováno v:
ICASSP
Adaptivity, stability, fast initial convergence, and low complexity are contradictory exigences in adaptive filtering. The least-mean-squares (LMS) algorithms suffer from a slow initial convergence, and the fast recursive least-squares (RLS) ones pre
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1c761173077a508e78544e79db56bca2
https://doi.org/10.1109/icassp.1986.1168766
https://doi.org/10.1109/icassp.1986.1168766
Autor:
G. Demoment, A. Houacine
Publikováno v:
ICASSP
Adaptive spectrum estimation is based on a local stationarity assumption for the studied process, and uses methods of the stationary case with data windows of reduced length. But conventional least squares methods and parsimony principle (for example
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::efcdbd70cf74f10b7b5fc3e852fbe64b
https://doi.org/10.1109/icassp.1987.1169313
https://doi.org/10.1109/icassp.1987.1169313
Publikováno v:
Fourth Annual ASSP Workshop on Spectrum Estimation and Modeling.
A method is described for the numerical analysis of nonstationary signals whose spectral distributions vary slowly enough with time for an adaptive method to be used. The data is processed by blocks. The theory describes the signal by an autoregressi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60eabff90cea38a673c850c75ba5037f
https://doi.org/10.1109/spect.1988.206158
https://doi.org/10.1109/spect.1988.206158