1 citations · 1 across the 4 of their papers we have counts for
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Nearly Optimum Properties of Certain Multi-Decision Sequential Rules for General Non-i.i.d. Stochastic Models
Alexander G. Tartakovsky
Dedicated to the memory of Professor Tze Leung Lai, this paper introduces three multi-hypothesis sequential tests. These tests are derived from one-sided versions of the sequential…
Minimax and pointwise sequential changepoint detection and identification for general stochastic models
Serguei Pergamenchtchikov, Alexander Tartakovsky, Valentin Spivak
This paper considers the problem of joint change detection and identification assuming multiple composite postchange hypotheses. We propose a multihypothesis changepoint detection-…
Optimal Sequential Detection of Signals with Unknown Appearance and Disappearance Points in Time
Alexander G. Tartakovsky, Nikita R. Berenkov, Alexei E. Kolessa +1
The paper addresses a sequential changepoint detection problem, assuming that the duration of change may be finite and unknown. This problem is of importance for many applications,…
An Asymptotic Theory of Joint Sequential Changepoint Detection and Identification for General Stochastic Models
Alexander G. Tartakovsky
The paper addresses a joint sequential changepoint detection and identification/isolation problem for a general stochastic model, assuming that the observed data may be dependent a…
Asymptotic Optimality of Mixture Rules for Detecting Changes in General Stochastic Models
Alexander G. Tartakovsky
The paper addresses a sequential changepoint detection problem for a general stochastic model, assuming that the observed data may be non-i.i.d. (i.e., dependent and non-identicall…
Asymptotically Optimal Quickest Change Detection In Multistream Data - Part 1: General Stochastic Models
Alexander Tartakovsky
Assume that there are multiple data streams (channels, sensors) and in each stream the process of interest produces generally dependent and non-identically distributed observations…