Results 241 to 250 of about 428,031 (297)

Long-Term Clinical Course and Progression Patterns of Normal-Tension Glaucoma Following Disc Hemorrhage. [PDF]

Invest Ophthalmol Vis Sci
Lee EJ, Kim H, Yoon J, Lee SJ, Kim TW.
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From stress to success: using physiological data to predict cardiopulmonary resuscitation simulation performance. [PDF]

Front Psychol
Queirolo L, Mormando G, Vittadello A, Cason G, Maino B, Pettenuzzo T, Sella N, Zarantonello F, Boscolo A, Zanette G, Navalesi P.   +10 more
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Multiscale geographically weighted modeling of tuberculosis incidence in China: integrating geographic perspectives into epidemiological analysis. [PDF]

Int J Health Geogr
Wang Z, Zhang J.
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Transient Flow Characterization between Matrix and Natural Fractures in Shale Oil Reservoir. [PDF]

ACS Omega
Wang Z, Wang S, Liu J, Zhang W, Xia D.
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Asymptotic Confidence Bands for Generalized Nonlinear Regression Models

Biometrics, 1995
Asymptotic confidence bands for generalized nonlinear regression models are developed. These are based on a combination of the S method of Scheffe, together with the delta method which is used to approximate the mean function by a linear combination of the parameters. The approach can be used in any situation where large sample theory can be applied to
Cox, Christopher, Ma, Guangqin
openaire   +3 more sources

A general framework for robust compressive sensing based nonlinear regression

2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012
In this paper, we present a general framework for robust nonlinear regression that leverages concepts from the field of compressive sensing to simultaneously detect outliers and determine optimally sparse representations of noisy data from arbitrary sets of basis functions.
Brian Moore, Balasubramaniam Natarajan
openaire   +1 more source

On generalized elliptical quantiles in the nonlinear quantile regression setup

TEST, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hlubinka, Daniel, Šiman, Miroslav
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Nonlinear process monitoring based on decentralized generalized regression neural networks

Expert Systems with Applications, 2020
Abstract Given that the main task of process monitoring (i.e., fault detection) is actually a classical one-class classification problem, the generalized regression neural network (GRNN) is directly inapplicable for handling process modeling and monitoring issues.
Ting Lan, Chudong Tong, Haizhen Yu, Xuhua Shi, Lijia Luo   +4 more
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Structural identifiability of generalized constraint neural network models for nonlinear regression

Neurocomputing, 2008
Identifiability becomes an essential requirement for learning machines when the models contain physically interpretable parameters. This paper presents two approaches to examining structural identifiability of the generalized constraint neural network (GCNN) models by viewing the model from two different perspectives.
Shuang-Hong Yang, Bao-Gang Hu, Paul-Henry Cournède   +2 more
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