نتایج جستجو برای: sequential gaussian co

تعداد نتایج: 491499  

Journal: :فیزیک زمین و فضا 0
کیوان نجف زاده دانشجوی کارشناسی ارشد، گروه فیزیک زمین، موسسه ژئوفیزیک، دانشگاه تهران، ایران محمدعلی ریاحی دانشیار، گروه فیزیک زمین، موسسه ژئوفیزیک دانشگاه تهران، ایران محسن سیدعلی کارشناس ارشد مهندسی اکتشاف نفت، تهران، ایران

permeability is a key parameter in reservoir characterization. in fact, without accurate information about reservoir permeability, there is no good solution for reservoir engineering problems. up to now, permeability values of a reservoir have been calculated through laboratory measurements or well testing methods. these methods are useful but they cannot describe a reservoir reliably and preci...

2005
Marco Chiani Maria G. Martini

We present a framework for the analysis of frame synchronization based on Synchronization Words (SWs), where the detection is based on the common sequential algorithm: the received samples are observed over a window of length equal to the SW; over this window a metric (e.g. correlation) is computed; a SW is declared if the computed metric is greater than a proper threshold, otherwise the observ...

Journal: :EURASIP J. Adv. Sig. Proc. 2002
Petar M. Djuric Jayesh H. Kotecha Fabien Esteve Etienne Perret

Parameter estimation of time-varying non-Gaussian autoregressive processes can be a highly nonlinear problem. The problem gets even more difficult if the functional form of the time variation of the process parameters is unknown. In this paper, we address parameter estimation of such processes by particle filtering, where posterior densities are approximated by sets of samples (particles) and p...

1999
Arnold Janssen

The paper establishes strong convergence results for the joint convergence of sequential order statistics. There exists an explicit construction such that almost sure convergence to extremal processes follows. If a partial sum of rowwise i.i.d. random variables is attracted by a non-Gaussian limit law then the results apply to invariance principles for sums of extreme sequential order statistic...

Reliable characterization of subsurface soil in urban areas is a major concern in geotechnical and geological engineering projects. In this regard, this research deals with development of a 3D geological engineering model on Mashhad City soil using Sequential Gaussian Simulation (SGS) approach. The intense variability of soil in the study area has sometimes caused serious problems in civil engi...

Journal: :Food microbiology 2010
Nancy Nehme Florence Mathieu Patricia Taillandier

The present study was aimed to evaluate the impact of the co-culture on the output of malolactic fermentation and to further investigate the reasons of the antagonism exerted by yeasts towards bacteria during sequential cultures. The Saccharomyces cerevisiae D strain/Oenococcus oeni X strain combination was tested by applying both sequential culture and co-culture strategies. This pair was chos...

Journal: :SIAM J. Control and Optimization 2015
Abhishek Gupta Serdar Yüksel Tamer Basar Cédric Langbort

In this paper, we identify sufficient conditions under which static teams and a class of sequential dynamic teams admit team-optimal solutions. We first investigate the existence of optimal solutions in static teams where the observations of the decision makers are conditionally independent given the state and satisfy certain regularity conditions. Building on these findings and the static redu...

2006
I. Escobar P. Williamson

We have developed an efficient stochastic AVA inversion technique that works directly in a fine-scale stratigraphic grid, and is conditioned by well data and multiple seismic angle stacks. We use a Bayesian framework and a linearized, weak contrast approximation of the Zoeppritz equation to construct a joint log-Gaussian posterior distribution for Pand S-wave impedances. We apply a Sequential G...

2016
Yali Wang Marcus Brubaker Brahim Chaib-draa Raquel Urtasun

In this section we briefly review sparse online GPs (GPso) [1, 2]. The key idea is to learn GPs recursively by updating the posterior mean and covariance of the training set {(x, y)}n=1 in a sequential fashion. This online procedure is coupled with a sparsification mechanism in which a fixed-size subset of the training set (called the active set) is iteratively selected to avoid the unbounded c...

2008
Trinh Minh Tri Do Thierry Artieres

This works deals with discriminant training of Gaussian Mixture Models through margin maximization. We go one step further previous work, we propose a new formulation of the learning problem that allows the use of efficient optimization algorithm popularized for Support Vector Machines, yielding improved convergence properties and recognition accuracy on handwritten digits recognition.

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