Topic
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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22 Oct 2018
TL;DR: A novel method for diagnosing gear crack in gearbox based on principal component analysis (PCA) and sequential probability ratio test (SPRT) and the results indicate that this method is feasible and practical to classify different conditions of the gearbox.
Abstract: This paper1 presents a novel method for diagnosing gear crack in gearbox based on principal component analysis(PCA) and sequential probability ratio test(SPRT). The vibration signal collected in the gearbox experimental system is denoised. The wavelet packet transform is suitable for the noise reduction to extract the features for the identification of the faulty gears. PCA is used to extract useful parameters of vibration signals. The parameter with the largest contribution rate after dimensionality reduction is chosen as the testing parameter of SPRT. The results indicate that this method is feasible and practical to classify different conditions of the gearbox.
3 citations
06 Jul 2008
TL;DR: In this article, the authors considered the problem of detecting a Markov signal when a variable number of noisy measurements can be taken and showed sufficient conditions for the validity of these properties are stated.
Abstract: The problem of detecting a Markov signal when a variable number of noisy measurements can be taken is here considered. In particular, the signal-observation sequence {Xi, Zi}iisinNopf is a hidden Markov model (HMM) and a sequential probability ratio test (SPRT) is used to detect {Xi, Zi}iisinNopf. It is known that the SPRT for testing simple hypotheses based on independent and identically distributed (i.i.d.) observations has a number of remarkable properties, the most appealing being the fact that it simultaneously minimizes the expected sample size under both hypotheses. These properties, however, may fail to hold as the observations {Zi}iisinNopf are not independent. In this paper sufficient conditions for the validity of these properties are stated. In particular, it is shown that under a set of rather mild conditions the test ends with probability one and its stopping time is almost surely minimized in the class of tests with the same or smaller error probabilities. Furthermore, reinforcing one of such conditions, it is also shown that any moment of the stopping time distribution is first-order asymptotically minimized in the same class of tests.
3 citations
TL;DR: In this article, the problem of evaluating a military or GPS/GSM system's precision quality is considered, where one sequentially observes bivariate normal data (X i, Y i ) and wants to test hypotheses on the circular error probability (CEP) or the probability of nonconforming, i.e., the probabilities of the system hitting or missing a pre-specified disk target.
3 citations
TL;DR: A sequential hypothesis testing approach is proposed for multi-frame detection and tracking of low-observable, maneuvering point-source targets in a digital image sequence and the resultant Multiple Multistage Hypothesis Test Tracking algorithm is proposed.
Abstract: A sequential hypothesis testing approach is proposed for multi-frame detection and tracking of low-observable, maneuvering point-source targets in a digital image sequence. The resultant Multiple Multistage Hypothesis Test Tracking (MMHTT) algorithm extends tracks formed from sequentially-detected target trajectory segments using a multiple hypothesis tracking strategy. Computational efficiency is achieved by using a truncated sequential probability ratio test (SPRT) to prune a dense tree of candidate target trajectories and score the detected trajectory segments. Results of an analytical evaluation of the algorithm's performance are discussed in relation to experimental results from an optical satellite tracking application.
3 citations
Patent•
23 Nov 2018
TL;DR: In this paper, the authors proposed a distance measurement-based security positioning method for solving the security positioning problem of a wireless sensor network. According to the method, the respective advantages of the proposed enhanced density clustering algorithm and hypothesis testing on the distance consistency are combined, the influences of malicious anchor nodes on the positioning process are eliminated by means of detection on the malicious anchors, and therefore the positioning validity is guaranteed.
Abstract: The invention provides a distance measurement-based security positioning method for solving the security positioning problem of a wireless sensor network. According to the method, the respective advantages of the proposed enhanced density clustering algorithm and hypothesis testing on the distance consistency are combined, the influences of malicious anchor nodes on the positioning process are eliminated by means of detection on the malicious anchor nodes, and therefore the positioning validity is guaranteed. According to the proposed MNDCC and EMNDCC algorithms, the four stages of data collection, adaptive multiple times of DBSCAN(Density-Based Spatial Clustering of Applications with Noise) clustering, detection model building and sequential probability ratio test are included, the malicious anchor nodes are detected by means of the characteristic that two measurement values (RSSI and TOA) of the distance have the consistency, the detection result is judged according to the sequentialprobability ratio test of a statistical decision, and therefore two types of errors (true abandon and false taking) are effectively reduced. According to the overall algorithm, the detection rate ofthe malicious anchor nodes is effectively increased, therefore, the positioning precision is improved, and the positioning validity is guaranteed.
3 citations