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George V. Moustakides

  1. Adaptive sampling for linear state estimation.

    Чт, 07/21/2011 - 15:01 — SomNambul
    Authors: George V. Moustakides, Maben Rabi, John S. Baras
    Subjects: Optimization and Control
    Abstract

    When a sensor has continuous measurements but sends limited messages over a
    data network to a supervisor which estimates the state, the available packet
    rate fixes the achievable quality of state estimation. When such rate limits
    turn stringent, the sensor's messaging policy should be designed anew. What are
    the good causal messaging policies ? What should message packets contain ? What
    is the lowest possible distortion in a causal estimate at the supervisor ? Is
    Delta sampling better than periodic sampling ?

  2. Joint Detection and Estimation: Optimum Tests and Applications.

    Чт, 01/27/2011 - 16:01 — SomNambul
    Authors: George V. Moustakides, Xiaodong Wang, Ali Tajer, Guido H. Jajamovich
    Subjects: Applications
    Abstract

    We consider a well defined joint detection and parameter estimation problem.
    By combining the Baysian formulation of the estimation subproblem with suitable
    constraints on the detection subproblem we develop optimum one- and two-step
    test for the joint detection/estimation case. The proposed combined strategies
    have the very desirable characteristic to allow for the trade-off between
    detection power and estimation efficiency. Our theoretical developments are
    then applied to the problems of retrospective changepoint detection and MIMO
    radar.

  3. A Numerical Approach to Performance Analysis of Quickest Change-Point Detection Procedures.

    Чт, 12/10/2009 - 16:01 — SomNambul
    Authors: Aleksey S. Polunchenko, Alexander G. Tartakovsky, George V. Moustakides
    Subjects: Computation
    Abstract

    For the most popular sequential change detection rules such as CUSUM, EWMA,
    and the Shiryaev-Roberts test, we develop integral equations and a concise
    numerical method to compute a number of performance metrics, including average
    detection delay and average time to false alarm. We pay special attention to
    the Shiryaev-Roberts procedure and evaluate its performance for various
    initialization strategies.

  4. Finite Sample Size Optimality of GLR Tests.

    Чт, 11/26/2009 - 16:01 — SomNambul
    Authors: George V. Moustakides
    Subjects: Statistics
    Abstract

    In several interesting applications one is faced with the problem of
    simultaneous binary hypothesis testing and parameter estimation. Although such
    joint problems are not infrequent, there exist no systematic analysis in the
    literature that treats them effectively. Existing approaches consider the
    detection and the estimation subproblems separately, applying in each case the
    corresponding optimum strategy. As it turns out the overall scheme is not
    necessarily optimum since the criteria used for the two parts are usually
    incompatible.

  5. Numerical Comparison of Cusum and Shiryaev-Roberts Procedures for Detecting Changes in Distributions.

    Пнд, 08/31/2009 - 17:16 — SomNambul
    Authors: Aleksey S. Polunchenko, Alexander G. Tartakovsky, George V. Moustakides
    Subjects: Computation
    Abstract

    The CUSUM procedure is known to be optimal for detecting a change in
    distribution under a minimax scenario, whereas the Shiryaev-Roberts procedure
    is optimal for detecting a change that occurs at a distant time horizon. As a
    simpler alternative to the conventional Monte Carlo approach, we propose a
    numerical method for the systematic comparison of the two detection schemes in
    both settings, i.e., minimax and for detecting changes that occur in the
    distant future.

  6. Decentralized Sequential Hypothesis Testing using Asynchronous Communication.

    Пнд, 08/31/2009 - 17:16 — SomNambul
    Authors: Georgios Fellouris, George V. Moustakides
    Subjects: Methodology
    Abstract

    We present a test for the problem of decentralized sequential hypothesis
    testing, which is asymptotically optimum. By selecting a suitable sampling
    mechanism at each sensor, communication between sensors and fusion center is
    asynchronous and limited to 1-bit data. The proposed SPRT-like test turns out
    to be order-2 asymptotically optimum in the case of continuous time and
    continuous path signals, while in discrete time this strong asymptotic
    optimality property is preserved under proper conditions. If these conditions
    do not hold, then we can show optimality of order-1.

Math-arch

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