Results 241 to 250 of about 85,871 (286)
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Coincidence of the Rao Test, Wald Test, and GLRT in Partially Homogeneous Environment
IEEE Signal Processing Letters, 2008This letter deals with the problem of detecting a signal known up to a scaling factor in the presence of partially homogeneous Gaussian disturbance with unknown covariance matrix. It is proved that the Rao test and the Wald test coincide with the generalized likelihood ratio test (GLRT) previously derived. Otherwise stated, the Rao test, the Wald test,
DE MAIO, ANTONIO, S. Iommelli
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Modified Rao Test for Multichannel Adaptive Signal Detection
IEEE Transactions on Signal Processing, 2016The problem of detecting a subspace signal is studied in colored Gaussian noise with an unknown covariance matrix. In the subspace model, the target signal belongs to a known subspace, but with unknown coordinates. We first present a new derivation of the Rao test based on the subspace model, and then propose a modified Rao test (MRT) by introducing a ...
Jun Liu +5 more
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The PAMF Detector is a Parametric Rao Test
Conference Record of the Thirty-Ninth Asilomar Conference onSignals, Systems and Computers, 2005., 2006 The Rao test for an adaptive signal detection prob- lem in space-time adaptive processing (STAP) applications is derived by modeling the disturbance signal as a multichannel autoregressive (AR) process. Interestingly, the Rao test takes a form identical to that of the recently introduced parametric adaptive matched filter (PAMF) detector.
Hongbin Li +2 more
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A new two-stage rao test detector
IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS, 2010In this paper, we propose a new two-stage Rao test detector, which is obtained by cascading a subspace detector (SD) and the Rao test. A set of secondary data is available and noise returns in primary and secondary data share the same statistical characterization.
Chengpeng Hao +3 more
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RAO: a low-cost AUV for testing
OCEANS 2000 MTS/IEEE Conference and Exhibition. Conference Proceedings (Cat. No.00CH37158), 2002We present an autonomous underwater vehicle (AUV) designed and assembled at the University of the Balearic Islands. This vehicle has been conceived to be a testing bench for the development of hardware and software related with underwater robotics.
G. Oliver +4 more
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Modified Rao test for adaptive subspace detection
IET International Radar Conference 2015, 2015The problem of detecting a subspace signal is studied in colored Gaussian noise with an unknown covariance matrix. In the subspace model, the target signal belongs to a known subspace, but with unknown coordinates. We first present a new derivation of the Rao test based on the subspace model, and then propose a modified Rao test (MRT) by introducing a ...
Jun Liu Jun Liu +2 more
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Rao's score test with nonparametric density estimators
Journal of Statistical Planning and Inference, 2001zbMATH Open Web Interface contents unavailable due to conflicting licenses.
González-Rivera, Gloria, Ullah, Aman
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Persymmetric Rao and Wald Tests for Partially Homogeneous Environment
IEEE Signal Processing Letters, 2012This letter deals with the problem of adaptive detection in partially-homogeneous Gaussian disturbance with unknown but persymmetric structured covariance matrix. Since no uniformly most powerful test exists for the problem at hand, we devise and assess two detection strategies based on the Rao test and the Wald test design criteria.
Hao C, Orlando D, Ma X, Hou C
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Burbea–Rao divergence based statistics for testing uniform association
Mathematics and Computers in Simulation, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jiménez-Gamero, M. D. +2 more
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Rao score tests for goodness of fit and independence
Biometrika, 1991Summary: Rao's score statistic [\textit{C. R. Rao}, Proc. Camb. Philos. Soc. 44, 50--57 (1948; Zbl 0034.07503)] is a standard tool for carrying out hypothesis tests. A unified approach is given which encompasses many common tests. When a suitable group structure is present, it is shown how the derivation of the test statistic can be simplified.
Mardia, K. V., Kent, J. T.
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