Results 271 to 280 of about 10,202,465 (303)

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
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A sequential likelihood ratio test for general hypotheses

Communications in Statistics. Part C: Sequential Analysis, 1982
In statistical inference it is often desired to test a specified funcrion of unkown parameters form an underlying distribution. Sequential procedures utilize information from the already collected observations and allow for a possible eariy termination of experimentation with a concurrent savings in time and cost. In the present work a suitable maximum-
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Improving the generalized likelihood ratio test for unknown linear gaussian channels

IEEE Transactions on Information Theory, 2003
Summary: We consider the decoding problem for unknown Gaussian linear channels. Important examples of linear channels are the intersymbol interference (ISI) channel and the diversity channel with multiple transmit and receive antennas employing space-time codes (STC).
Elona Erez, Meir Feder
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A Reduced-Rank Generalized Likelihood-Ratio Test

1993
A generalized likelihood-ratio test (GLRT) is proposed for adaptively detecting a low rank signal in the presence of unknown strong low rank interference plus white Gaussian noise. This approach leads to a test which is closely related to the Principal Component Inverse (PCI) method of rapidly adaptive detection and extends the PCI method to the case ...
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Generalized Likelihood Ratio Test Performance for Cooperative Radar-Communications

2018 52nd Asilomar Conference on Signals, Systems, and Computers, 2018
The performance of generalized likelihood ratio tests (GLRT) in radar detection is a well-studied subject, as is the performance of a maximum-likelihood decoder for a communication (comm.) receiver. The theoretical analysis of a cooperative radar-comm. receiver, however, remains an open problem.
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A bootstrap generalized likelihood ratio test in discriminant analysis

Computational Statistics & Data Analysis, 1996
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Gray, H. L., Baek, J., Woodward, W. A., Miller, J., Fisk, M.   +4 more
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Generalized Likelihood Ratio Tests and Uniformly Most Powerful Tests

The American Statistician, 1990
Abstract For testing a one-sided hypothesis in a one-parameter family of distributions, it is shown that the generalized likelihood ratio (GLR) test coincides with the uniformly most powerful (UMP) test, assuming certain monotonicity properties for the likelihood function.
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Robustness of generalized likelihood ratio test for linear regression

IFAC Proceedings Volumes, 2003
Abstract Some properties of the generalized likelihood ratio (GLR) test for fault detection are discussed in the framework of linear regression with Gaussian noise. It is pointed out that the GLR test with a carefully designed numerical algorithm is robust against unsufficient excitations. This robustness is compared with that of the detection method
Qingbua Zhang, Michèle Basseville
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The Rao, Wald, And Likelihood-Ratio Tests under Generalized Self-Concordance

ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
Three classical approaches to goodness-of-fit testing are Rao’s test, Wald’s test, and the likelihood-ratio test. The asymptotic equivalence of these three tests under the null hypothesis is a famous connection in statistical detection theory. We revisit these three likelihood-related tests from a non-asymptotic viewpoint under self-concordance ...
Lang Liu, Zaïd Harchaoui
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Generalized linear and generalized additive models in studies of species distributions: setting the scene

Ecological Modelling, 2002
Antoine Guisan, Thomas C Edwards
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