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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.


Papers
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Proceedings ArticleDOI
26 Jun 2011
TL;DR: The new spatial diversity with sequential maximal ratio combining (S-MRC) is proposed and analyzed and is more power-saving than the traditional MRC or the output-threshold MRC (OT) or a truncated sequential probability ratio test (TSPRT).
Abstract: A new spatial diversity with sequential maximal ratio combining (S-MRC) is proposed and analyzed. In the S-MRC system, the diversity branches are added for combining one-by-one in a sequential manner, and a truncated sequential probability ratio test (TSPRT) is used for signal detection. By sequentially adding individual branches for combining, the power consumption from directly using all available branches can be saved. The S-MRC is more power-saving than the traditional MRC or the output-threshold MRC (OT-MRC). Numerical results for the bit error rate (BER) of the BPSK signaling over the independently and identically distributed (i.i.d.) Rayleigh fading channels are presented to illustrate the performance of the S-MRC which is much better than the OT-MRC and is identical to that of the traditional MRC if a suitable test threshold is used. Furthermore, the average number of active branches is much smaller than that of the traditional MRC.

3 citations

Book ChapterDOI
01 Jan 2006
TL;DR: This paper proposes a simple, and easy to design, special case of sequential sampling plans by attributes, named CSeq-1 sampling plans, having acceptance numbers not greater than one, and analyzes the properties of these plans.
Abstract: Acceptance sampling plans have been widely used in statistical quality control for several decades. However, when nearly perfect quality is needed, their practicability is questioned by practitioners because of required large sample sizes. Moreover, the majority of well-known sampling plans allow nonconforming items in a sample, and this contradicts the generally accepted “zero defect” paradigm. Sequential sampling plans, introduced by Wald [7], assure the lowest possible sample size. Thus, they are applicable especially for sampling products of high quality. Unfortunately, their design is rather complicated. In the paper we propose a simple, and easy to design, special case of sequential sampling plans by attributes, named CSeq-1 sampling plans, having acceptance numbers not greater than one. We analyze the properties of these plans, and compare them to the properties of other widely-used sampling procedures.

3 citations

Journal Article
TL;DR: This paper proposed the performance of SPRT on Interval domain data using Weibull model and analyzed the results by applying on 5 data sets and estimated the parameters using Maximum Likelihood Estimation.
Abstract: In Classical Hypothesis testing volumes of data is to be collected and then the conclusions are drawn which may take more time. But, Sequential Analysis of statistical science could be adopted in order to decide upon the reliable / unreliable of the developed software very quickly. The procedure adopted for this is, Sequential Probability Ratio Test (SPRT). In the present paper we proposed the performance of SPRT on Interval domain data using Weibull model and analyzed the results by applying on 5 data sets. The parameters are estimated using Maximum Likelihood Estimation

3 citations

Proceedings Article
22 Feb 2012
TL;DR: This paper proposes a smart design strategy for a sequential detector to reliably detect the primary user’s signal, especially in fast fading environments, and proposes an efficient sensing algorithm for performing the sequential probability ratio test in a robust and ef-cient manner when the channel statistics are unknown.
Abstract: This paper proposes a smart design strategy for a sequential detector to reliably detect the primary user’s signal, especially in fast fading environments. We study the computation of the log-likelihood ratio for coping with a fast changing received signal and noise sample variances, which are considered random variables. First, we analyze the detectability of the conventional generalized log-likelihood ratio (GLLR) scheme when considering fast changing statistics of unknown parameters caused by fast fading effects. Secondly, we propose an efficient sensing algorithm for performing the sequential probability ratio test in a robust and efficient manner when the channel statistics are unknown. Finally, the proposed scheme is compared to the conventional method with simulation results with respect to the average number of samples required to reach a detection decision. Keywords—Cognitive radio, fast fading, sequential detection, spectrum sensing.

3 citations

Proceedings ArticleDOI
01 Mar 2019
TL;DR: The signal processing model and basic inspection strategy of nuclide recognition method based on statistical test, a Monte Carlo method to select the test threshold is proposed, and a radionuclide characteristic gamma-ray identifier for137Cs based on Wald sequential probability ratio test is constructed.
Abstract: Radionuclide detection is a key step in the control of radioactive materials. Influenced by detector performance, ambient background noise and data analysis model, fast identification of radionuclides is a great challenge faced by traditional gamma-ray spectrometry analysis methods. This paper introduces the signal processing model and basic inspection strategy of nuclide recognition method based on statistical test, a Monte Carlo method to select the test threshold is proposed, and a radionuclide characteristic gamma-ray identifier for137Cs based on Wald sequential probability ratio test is constructed. In the end, the detection performance of the identifier is analyzed through emulate experiment.

3 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20236
202223
202129
202023
201929
201832