Sequential Joint Detection and Estimation: Optimum Tests and Applications

Sequential Joint Detection and Estimation ∗

We consider the problem of simultaneous detection and estimation under a sequential framework. In particular, we are interested in sequential tests that distinguish between the null and the alternative hypothesis, and every time the decision is in favor of the alternative they provide an estimate of a random parameter. As we demonstrate with our analysis, treating the two subproblems separately...

Sequential Methods and Their Applications

Asymptotically optimum tests for decentralized change detection

Assuming that sensors have full local memory, we introduce a novel test for the problem of decentralized change detection that is asymptotically optimum. According to our proposed scheme, sensors perform locally repeated SPRTs and communicate, asynchronously, their one-bit decisions to a fusion center. The fusion center in turn uses the sequentially acquired information to perform a CUSUM test ...

Sequential Locally Optimum Test (SLOT): A Sequential Detection Scheme Based on Locally Optimum Test Statistic

Based on the characteristics of the thresholds of two detection schemes employing locally optimum test statistics, a sequential detection design procedure is proposed and analyzed. The proposed sequential test, called the sequential locally optimum test (SLOT), inherently provides finite stopping time (terminates with probability one within the finite horizon), and thereby avoids undesirable fo...

Sequential Detection and Estimation of Change-Points

In this report the problem of sequential detection and estimation of change-points is considered. The sense of this problem is as follows: in practice after raising an alarm signal about a change it is often required to divide the whole obtained sequential sample into subsamples of observations before and after an unknown change-point. In this report asymptotically optimal methods are proposed ...