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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.
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TL;DR: The results of this study reveal that the SPRT chart is more effective than the CUSUM chart and X¯ chart by 58% and 126%, respectively, from an overall viewpoint.
111 citations
TL;DR: It is shown that for a certain criterion of optimality, this generalized Shiryayev SPRT detects and isolates a change in hypothesis in the conditionally independent measurement sequence in minimum time, unlike the Wald SPRT, which assumes the entire measurement sequence to correspond to a single hypothesis.
Abstract: The authors derive an online multiple hypothesis Shiryayev sequential probability ratio test (SSPRT) by adopting a dynamic programming approach. It is shown that for a certain criterion of optimality, this generalized Shiryayev SPRT detects and isolates a change in hypothesis in the conditionally independent measurement sequence in minimum time, unlike the Wald SPRT, which assumes the entire measurement sequence to correspond to a single hypothesis. The measurement cost, the cost of a false alarm, and the cost of a miss-alarm are considered in our dynamic programming analysis. The algorithm is shown to be optimal in the infinite time case. Finally, the performance of the algorithm is evaluated by using a few examples. In particular, they implement the algorithm in a fault detection and identification scheme for advanced vehicle control systems.
110 citations
TL;DR: In this article, the authors present the explicit solution of the Bayesian problem of sequential testing of two simple hypotheses about the intensity of an observed Poisson process, which consists of reducing the initial problem to a free-boundary differential-difference problem, and solving the latter by use of the principles of smooth and continuous fit.
Abstract: We present the explicit solution of the Bayesian problem of sequential testing of two simple hypotheses about the intensity of an observed Poisson process. The method of proof consists of reducing the initial problem to a free-boundary differential-difference Stephan problem, and solving the latter by use of the principles of smooth and continuous fit. A rigorous proof of the optimality of the Wald’s sequential probability ratio test in the variational formulation of the problem is obtained as a consequence of the solution of the Bayesian problem.
106 citations
TL;DR: This paper presents a model for the reproduction of temporal intervals, with particular emphasis on the sequential statistics of a series of such reproductions, and provides a quantitative account of the pattern of autocorrelation found in aseries of RTs.
106 citations
28 Sep 2004
TL;DR: Simulation and experimental results, from using a camera as the bearing-only sensor mounted on a Pioneer robot are included to demonstrate the effectiveness of the proposed technique.
Abstract: This paper presents a multiple hypothesis approach to solve the simultaneous localisation and mapping (SLAM) problem with a bearing-only sensor. The main contribution of the paper is to provide a remedy for the landmark initialisation problem that occurs due to the absence of range information, in a computationally efficient manner. Each landmark is initialised in the form of multiple hypotheses distributed along the direction of the bearing measurement. Using subsequent measurements, the validity of the hypotheses is evaluated based on the sequential probability ratio test (SPRT). Consequently, the best approximation to the landmark location is maintained. This approach enables an extended Kalman filler (EKF) to be used for bearing-only SLAM providing a computational efficient solution. Simulation and experimental results, from using a camera as the bearing-only sensor mounted on a Pioneer robot are included to demonstrate the effectiveness of the proposed technique.
102 citations