Results 241 to 250 of about 163,645 (292)

Comments on: Nonparametric inference with generalized likelihood ratio tests

TEST, 2007
In our discussion we make remarks on the range of the validity of Wilks phenomenon and address the question if one should always try to reach Wilks phenomenon. We discuss the need of bias corrections in test statistics, make some power considerations, and mention some open problems.
Raymond J. Carroll, Arnab Maity
  +6 more sources

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
openaire   +1 more source

New Approximate Distributions for the Generalized Likelihood Ratio Test Detection in Passive Radar

IEEE Signal Processing Letters, 2019
Generalized likelihood ratio test is an effective method for target detection in passive radar systems. The distribution of its decision variable in the presence of a direct path is unknown but is required for the calculation of the detection threshold ...
Yunfei Chen, Yue Wu, Ning Chen, W. Feng, Jie Zhang   +4 more
semanticscholar   +1 more source

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 ...
den Dekker, Arnold J., Sijbers, Jan
openaire   +3 more sources

Generalized and Differential Likelihood Ratio Tests with Quantum Signal Processing

ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019
Quantum signal processing invokes the injection of abstract quantum mechanical frameworks into classical signal processing problems. In this work we apply this idea to the notion of optimal likelihood ratio tests within the context of the location verification problem.
Shihao Yan, Robert A. Malaney, Jinhong Yuan   +2 more
openaire   +1 more source

Generalized Likelihood Ratios for Testing the Properness of Quaternion Gaussian Vectors

IEEE Transactions on Signal Processing, 2011
In a recent paper, the second-order statistical analysis of quaternion random vectors has shown that there exist two different kinds of quaternion widely linear processing, which are associated with the two main types of quaternion properness. In this paper, we consider the problem of determining, from a finite number of independent vector observations,
Javier Vía, Daniel P. Palomar, Luis Vielva   +2 more
openaire   +2 more sources

Kernel Generalized Likelihood Ratio Test for Fault Detection of Biological Systems

IEEE Transactions on Nanobioscience, 2018
In this paper, we develop an improved fault detection (FD) technique in order to enhance the monitoring abilities of nonlinear biological processes. Generalized likelihood ratio test (GLRT)-based kernel principal component analysis (KPCA) (called also ...
M. Mansouri, Raoudha Baklouti, M. Harkat, M. Nounou, H. Nounou, A. Hamida   +5 more
semanticscholar   +1 more source

On the generalized likelihood ratio test for a class of nonlinear detection problems

IEEE Transactions on Signal Processing, 1993
The authors examine the generalized likelihood ratio test (GLRT) for a certain class of detection problems. This class is characterized by a model which is linear in some parameters and nonlinear in others. They show that the classical asymptotic analysis of the GLRT fails for this class, and demonstrate the existence of ill-behaved cases in this class.
Boaz Porat, Benjamin Friedlander
openaire   +1 more source

Generalized and Average Likelihood Ratio Testing for Post Detection Integration

IEEE Transactions on Communications, 2007
In the context of spread spectrum communications, this paper investigates the use of likelihood ratio testing techniques for the design of post detection integration (PDI) methods for code acquisition in the presence of phase and frequency uncertainty.
CORAZZA, GIOVANNI EMANUELE, PEDONE, RAFFAELLA   +1 more
openaire   +2 more sources