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Nestimate: An R Package for dynamic, probabilistic, and high order network analysis. [PDF]
Appl Psychol MeasSaqr M, López-Pernas S, Misiejuk K.
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Enhancing completeness and forecasting of early post-mainshock sequences: A case study of the 2021 Qinghai Maduo <i>M</i> <sub>S</sub>7.4 earthquake. [PDF]
iScienceBi J, Li Y, Gao Y, Pan Y.
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Process Phase Estimation and Deviation Detection for Manual Soldering Based on Motion Analysis. [PDF]
Biomimetics (Basel)Wakabayashi K, Oda T.
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Forensic Age Estimation of the Knee with 3D MEDIC MRI. [PDF]
Diagnostics (Basel)Yabul FC +5 more
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An AR 3D Tracking and Registration Method That Integrates Optical Flow Tracking and Mean Shift. [PDF]
Sensors (Basel)Yong J, Lei X, Dang J.
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2007 41st Annual Conference on Information Sciences and Systems, 2007
Recent work in the theory of subspace filtering and estimation, for example the Multistage Wiener Filter (MWF) of Goldstein et. al., has focused primarily on the case of finite dimension filtering. While this is the more practical case, as it can be implemented in a general purpose computer, it has left open the theoretical question of the behavior of ...
Michael Tinston, Yariv Ephraim
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Recent work in the theory of subspace filtering and estimation, for example the Multistage Wiener Filter (MWF) of Goldstein et. al., has focused primarily on the case of finite dimension filtering. While this is the more practical case, as it can be implemented in a general purpose computer, it has left open the theoretical question of the behavior of ...
Michael Tinston, Yariv Ephraim
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Quantile Estimation in Dependent Sequences
Operations Research, 1984Standard nonparametric estimators of quantiles based on order statistics can be used not only when the data are i.i.d., but also when the data are drawn from a stationary, ϕ-mixing process of continuous random variables. However, when the random variables are highly positively correlated, the sample sizes needed for estimating extreme quantiles become
Philip Heidelberger, Peter A. W. Lewis
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Estimating motion in image sequences
IEEE Signal Processing Magazine, 1999We have reviewed the estimation of 2D motion from time-varying images, paying particular attention to the underlying models, estimation criteria, and optimization strategies. Several parametric and nonparametric models for the representation of motion vector fields and motion trajectory fields have been discussed.
Christoph Stiller, Janusz Konrad
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IEEE Transactions on Communications, 1995
Summary: Estimating the data sequence from the received signal without knowing the transmission channel is referred to as blind sequence estimation. A new blind sequence estimation scheme is proposed by exploiting the second order statistical properties of the source and the algebraic structures of the data sequence.
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Summary: Estimating the data sequence from the received signal without knowing the transmission channel is referred to as blind sequence estimation. A new blind sequence estimation scheme is proposed by exploiting the second order statistical properties of the source and the algebraic structures of the data sequence.
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On the threshold effect in the estimation of chaotic sequences
The 22nd Convention on Electrical and Electronics Engineers in Israel, 2002., 2003Chaotic sequences and chaotic dynamic systems are attractive candidates for use in signal modelling, synthesis, and analysis as well as in communications applications. In most of the above applications, there is a frequent need to estimate the chaotic sequence from noisy observations.
Ilan Hen, Neri Merhav
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