Echo Cancellation : the generalized likelihood ratio test for double-talk vs. channel change

Echo cancellers are required in both electrical (impedance mismatch) and acoustic (speaker-microphone coupling) applications. One of the main design problems is the control logic for adaptation. Basically, the algorithm weights should be frozen in the presence of double-talk and adapt quickly in the absence of double-talk. The optimum likelihood ratio test (LRT) for this problem was studied in a recent paper. The LRT requires a priori knowledge of the background noise and double-talk power levels. Instead, this paper derives a generalized log likelihood ratio test (GLRT) that does not require this knowledge. The probability density function of a sufficient statistic under each hypothesis is obtained and the performance of the test is evaluated as a function of the system parameters. The receiver operating characteristics (ROCs) indicate that it is difficult to correctly decide between double-talk and a channel change, based upon a single look. However, detection based on about 200 successive samples yields a detection probability close to unity (0.99) with a small false alarm probability (0.01) for the theoretical GLRT model. Application of a GLRT-based echo canceller (EC) to real voice data shows comparable performance to that of the LRT-based EC given in a recent paper

Cancelable ECG Biometrics using Compressive Sensing-Generalized Likelihood Ratio Test

Electrocardiogram (ECG) has been investigated as promising biometrics, but it cannot be canceled and re-used once compromised just like other biometrics. We propose methods to overcome the issue of irrevocability in ECG biometrics without compromising performance. Our proposed cancelable user authentication uses a generalized likelihood ratio test (GLRT) based on a composite hypothesis testing in compressive sensing (CS) domain We also propose a permutation-based revocation method for CS-based cancelable biometrics so that it becomes resilient to record multiplicity attack. In addition, to compensate for inevitable performance degradation due to cancelable schemes, we also propose two performance improvement methods without undermining cancelable schemes: a self-guided ECG filtering and a T-wave shift model in our CS-GLRT. Finally, our proposed methods were evaluated for various cancelable biometrics criteria with the public ECG-ID data (89 subjects). Our cancelable ECG biometric methods yielded up to 93.0% detection probability at 2.0% false alarm ratio (PD*) and 3.8% equal error rate (EER), which are comparable to or even better than non-cancelable baseline with 93.2% PD* and 4.8% EER for challenging single pulse ECG authentication, respectively. Our proposed methods met all cancelable biometrics criteria theoretically or empirically. Our cancelable secure user template with our novel revocation process is practically non-invertible and robust to record multiplicity attack

A generalized likelihood ratio test statistic for Cherenkov telescope data

Astrophysical sources of TeV gamma rays are usually established by Cherenkov telescope observations. These counting type instruments have a field of view of few degrees in diameter and record large numbers of particle air showers via their Cherenkov radiation in the atmosphere. The showers are either induced by gamma rays or diffuse cosmic ray background. The commonly used test statistic to evaluate a possible gamma-ray excess is Li and Ma (1983), Eq. 17, which can be applied to independent on- and off-source observations, or scenarios that can be approximated as such. This formula however is unsuitable if the data are taken in so-called "wobble" mode (pointing to several offset positions around the source), if at the same time the acceptance shape is irregular or even depends on operating parameters such as the pointing direction or telescope multiplicity. To provide a robust test statistic in such cases, this paper explores a possible generalization of the likelihood ratio concept on which the formula of Li and Ma is based. In doing so, the multi-pointing nature of the data and the typically known instrument point spread function are fully exploited to derive a new, semi-numerical test statistic. Due to its flexibility and robustness against systematic uncertainties, it is not only useful for detection purposes, but also for skymapping and source shape fitting. Simplified Monte Carlo simulations are presented to verify the results, and several applications and further generalizations of the concept are discussed.Comment: 27 pages, 8 figure

The adaptive coherence estimator is the generalized likelihood ratio test for a class of heterogeneous environments

The adaptive coherence estimator (ACE) is known to be the generalized likelihood ratio test (GLRT) in partially homogeneous environments, i.e., when the covariance matrix Ms of the secondary data is proportional to the covariance matrix Mp of the vector under test (or Ms = gamma/Mp). In this letter, we show that ACE is indeed the GLRT for a broader class of nonhomogeneous environments, more precisely when Ms is a random matrix, with inverse complex Wishart prior distribution whose mean only is proportional to Mp. Furthermore, we prove that, for this class of heterogeneous environments, the ACE detector satisfies the constant false alarm rate (CFAR) property with respect to gamma and Mp

The evaluation of failure detection and isolation algorithms for restructurable control

Three failure detection and identification techniques were compared to determine their usefulness in detecting and isolating failures in an aircraft flight control system; excluding sensor and flight control computer failures. The algorithms considered were the detection filter, the Generalized Likelihood Ratio test and the Orthogonal Series Generalized Likelihood Ratio test. A modification to the basic detection filter is also considered which uses secondary filtering of the residuals to produce unidirectional failure signals. The algorithms were evaluated by testing their ability to detect and isolate control surface failures in a nonlinear simulation of a C-130 aircraft. It was found that failures of some aircraft controls are difficult to distinguish because they have a similar effect on the dynamics of the vehicle. Quantitative measures for evaluating the distinguishability of failures are considered. A system monitoring strategy for implementing the failure detection and identification techniques was considered. This strategy identified the mix of direct measurement of failures versus the computation of failure necessary for implementation of the technology in an aircraft system

Generalized Likelihood Signal Resolution

This Paper Defines an M-Ary Generalized Likelihood Ratio Test (MGLRT) that overcomes Root\u27s Early Objection to the Application of Generalized Likelihood Ratio Testing to the Resolution of Correlated Signals. the Proposed Test Extends the Form of a Conventional Binary Generalized Likelihood Ratio Test (GLRT) in a Manner that Permits a Generalization of the Minimax Properties of the Binary Test to the M-Hypotheses Case. When the Estimated Signals Are Orthogonal, the Test Reduces to a Sequence of Conventional Binary Tests Duplicating the Performance of a Narrow-Band Matched Filter Envelope-Detector Receiver. © 1975, IEEE. All Rights Reserved