Sequential probability ratio test

About: Sequential probability ratio test is a research topic. Over the lifetime, 1248 publications have been published within this topic receiving 22355 citations.

Sequential Probability Ratio Test for Collision Avoidance Maneuver Decisions

Abstract: When facing a conjunction between space objects, decision makers must chose whether to maneuver for collision avoidance or not. We apply a well-known decision procedure, the sequential probability ratio test, to this problem. We propose two approaches to the problem solution, one based on a frequentist method, and the other on a Bayesian method. The frequentist method does not require any prior knowledge concerning the conjunction, while the Bayesian method assumes knowledge of prior probability densities. Our results show that both methods achieve desired missed detection rates, but the frequentist method's false alarm performance is inferior to the Bayesian method's

Adaptive sequential Bayesian classification using Page's test

Abstract: In this paper, the previously introduced Mean-Field Bayesian Data Reduction Algorithm is extended for adaptive sequential hypothesis testing utilizing Page's test. In general, Page's test is well understood as a method of detecting a permanent change in distribution associated with a sequence of observations. However, the relationship between detecting a change in distribution utilizing Page's test with that of classification and feature fusion is not well understood. Thus, the contribution of this work is based on developing a method of classifying an unlabeled vector of fused features (i.e., detect a change to an active statistical state) as quickly as possible given an acceptable mean time between false alerts. In this case, the developed classification test can be thought of as equivalent to performing a sequential probability ratio test repeatedly until a class is decided, with the lower log-threshold of each test being set to zero and the upper log-threshold being determined by the expected distance between false alerts. It is of interest to estimate the delay (or, related stopping time) to a classification decision (the number of time samples it takes to classify the target), and the mean time between false alerts, as a function of feature selection and fusion by the Mean-Field Bayesian Data Reduction Algorithm. Results are demonstrated by plotting the delay to declaring the target class versus the mean time between false alerts, and are shown using both different numbers of simulated training data and different numbers of relevant features for each class.

Performance analysis and robustness evaluation of a sequential probability ratio test for non-identically distributed observations

Abstract: In this article the problem of a sequential test for the model of independent non-identically distributed observations is considered. Based on recursive calculation a new numerical approach to approximate test characteristics for a sequential probability ratio test (SPRT) and a truncated SPRT (TSPRT) is constructed. The problem of robustness evaluation is also studied when the contamination is presented by the distortion of the distributions of all increments of the log-likelihood ratio statistics. The two-side truncated functions are proposed to be used for constructing the robustified SPRT. An algorithm to choose the thresholds of these truncated functions is indicated. The results are applied for a sequential test on parameters of time series with trend. Some kinds of the contaminated models of time series with trend are used to study the robustness of the truncated SPRT. Numerical examples confirming the theoretical results mentioned above are given.

Modeling of IC Socket Contact Resistance for Reliability and Health Monitoring Applications

Abstract: We present a methodology based on the physics of failure, and the sequential probability ratio test, for modeling and monitoring electrical interconnects in health monitoring, and electronic prognostic applications. The resistance behavior of an electrical contact was characterized as a function of temperature. The physics of failure of the contact technology were analysed. A contact resistance model was selected, and its parameters were fitted using the temperature characterization data. The physics of failure model was evaluated with a reliability application (temperature cycle test), and was found to produce estimation errors of < 1 mOmega of during a training period. The temperature and resistance of ten sample contacts were continuously monitored during the temperature cycle test, identifying the maximum temperature and resistances for each cycle. Using the physics of failure model, maximum resistance estimates were generated for each test sample. The residual between the monitored and estimated resistance values was evaluated with the sequential probability ratio test. The method was shown to overcome the issues of traditional threshold-based monitoring approaches, providing accurate resistance estimates, and allowing the detection of abnormal resistance behavior with low false alarm and missed alarm probabilities.

A Fault Diagnosis Method of Temperature Sensor Based on Analytical Redundancy

Abstract: Fault diagnosis technology of the temperature sensor on the general processing module (GPM) of integrated modular avionics (IMA) was studied. Through the accelerated life testing of the complex programmable logic device (CPLD) on GPM, the corresponding analytical relationship between the oscillator frequency and temperature was obtained, and the analytical redundancy model between temperature and oscillator frequency was constructed. The fault diagnosis algorithm is designed based on statistical hypothesis testing. The moving mean method is used in the alarm process. The paper compares the traditional method WSPRT (Wald Sequential Probability Ratio Test) with MaxSPRT in the verification process. For MaxSPRT, its hypothesis testing model of the normal distribution is deduced. The simulation model of sensor fault is designed. The effectiveness and rapidity of the proposed method are verified.