Results 241 to 250 of about 387,662 (285)

Generalized likelihood ratio tests for complex fMRI data

SPIE Proceedings, 2004
Functional magnetic resonance imaging (fMRI) intends to detect significant neural activity by means of statistical data processing. Commonly used statistical tests include the Student-t test, analysis of variance, and the generalized linear model test. A key assumption underlying these methods is that the data are Gaussian distributed.
Sijbers, J. (author), Den Dekker, A.J. (author)   +1 more
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A generalized likelihood ratio test for impropriety of complex signals

IEEE Signal Processing Letters, 2006
A complex random vector is called improper if it is correlated with its complex conjugate. We present a hypothesis test for impropriety based on a generalized likelihood ratio (GLR). This GLR is invariant to linear transformations on the data, including rotation and scaling, because propriety is preserved by linear transformations.
Peter J. Schreier, Louis L. Scharf, Alfred Hanssen   +2 more
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Adaptive selection method for generalized likelihood ratio test

IEEE Transactions on Aerospace and Electronic Systems, 2015
The generalized likelihood ratio test (GLRT) for spatial diversity detection is widely used in target detection problems in multiple input, multiple output (MIMO) radar systems. GLRT is derived using the probability density function (pdf) of the noise signal in a homogeneous noise environment.
Minjae Park 0002, Hwang Soo Lee
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A full generalized likelihood ratio test for source detection

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012
This work presents a novel full generalized likelihood ratio test (GLRT) for signal detection in a sensor array environment. The multiple hypothesis test approach is well known to have excellent detection performance among several popular methods. Existing multiple test procedures consider the relation between two adjacent models.
Pei-Jung Chung, Kon Max Wong
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A nonlinear version of the generalized likelihood ratio test

Proceedings of the 33rd Chinese Control Conference, 2014
In this paper, a new version of the generalized likelihood ratio (GLR) test is proposed to deal with the fault diagnosis problem in nonlinear systems. The unscented Kalman filter (UKF) is utilized for state estimation and innovation generation. The fault signatures used in the hypotheses test are pre-computed by running the fault model and the nominal ...
Hai Liu, Maiying Zhong
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Generalized Likelihood Ratio Test for GNSS Spoofing Detection in Devices With IMU

IEEE Transactions on Information Forensics and Security, 2021
Spoofing attacks in global navigation satellite systems (GNSSs) aim at inducing the estimation of a fake position at the victim receiver. Many devices, including smartphones, are nowadays equipped with both a GNSS receiver and an inertial measurement unit (IMU), which also provides location/movement information, while being immune from GNSS attacks. We
Ceccato M., Formaggio F., Laurenti N., Tomasin S.   +3 more
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Generalized likelihood ratio test for normal mixtures

Statistica Sinica, 2016
Summary: Let \(X_{1},\ldots,X_{n}\) be independent observations with \(X_{i} \sim N(\theta_{i},1)\), where \((\theta_{1},\ldots,\theta_{n})\) is an unknown vector of normal means. Let \(f_{n}(x) = \sum_{i=1}^{n}(d/dx)P_{n}\{X_{i}\leq x\}/n\) be the average marginal density of observations.
Jiang, Wenhua, Zhang, Cun-Hui
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Nonparametric inference with generalized likelihood ratio tests

TEST, 2007
The advance of technology facilitates the collection of statistical data. Flexible and refined statistical models are widely sought in a large array of statistical problems. The question arises frequently whether or not a family of parametric or nonparametric models fit adequately the given data.
Jianqing Fan, Jiancheng Jiang
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Generalized likelihood ratio tests for complex fMRI data: a Simulation study

IEEE Transactions on Medical Imaging, 2005
Statistical tests developed for the analysis of (intrinsically complex valued) functional magnetic resonance time series, are generally applied to the data's magnitude components. However, during the past five years, new tests were developed that incorporate the complex nature of fMRI data.
Jan Sijbers, Arnold J. den Dekker
openaire   +4 more sources

Implications of the Rician distribution for fMRI generalized likelihood ratio tests

Magnetic Resonance Imaging, 2005
In functional magnetic resonance imaging (fMRI), the general linear model test (GLMT) is widely used for brain activation detection. However, the GLMT relies on the assumption that the noise corrupting the data is Gaussian distributed. Because the majority of fMRI studies employ magnitude image reconstructions, which are Rician distributed, this ...
Arnold J, den Dekker, Jan, Sijbers
openaire   +2 more sources