Title :
Random Distortion Testing and applications
Author :
Pastor, Dominique ; Quang-Thang Nguyen
Author_Institution :
Inst. Telecom, Univ. Eur. de Bretagne, Brest, France
Abstract :
We address Random Distortion Testing (RDT), that is, the problem of testing whether the Mahalanobis distance between a random signal Θ and a known deterministic model θ0 exceeds some given τ ≥ 0 or not, when Θ has unknown probability distribution and is observed in additive independent Gaussian noise with positive definite covariance matrix. A suitable optimality criterion for RDT is presented and theoretical results on optimal tests for this criterion are given. Several applications of these results are presented and analyzed. They address the detection of signals in case of model mismatch and the detection of deviations from model θ0.
Keywords :
Gaussian noise; covariance matrices; signal detection; Mahalanobis distance; additive independent Gaussian noise; deterministic model; event testing; hypothesis testing; positive definite covariance matrix; probability distribution; random distortion testing; random signal; signal detection; Covariance matrices; Distortion; Signal to noise ratio; Standards; Testing; Tin; Event testing; Mahalanobis norm; hypothesis testing; invariance; random distortion testing; test with maximal constant conditional power;
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
DOI :
10.1109/ICASSP.2013.6638887
