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Information Journal Paper

Title

OPTIMUM LOCAL DECISION DECISION RULES IN A DISTRIBUTED DETECTION SYSTEM WITH DEPENDENT OBSERVATIONS

Pages

  1-10

Abstract

 The theory of DISTRIBUTED DETECTION is receiving a lot of attention. A common assumption used in previous studies the conditional independence of the observation. In this paper, the optimization of local DISTRIBUTED DETECTION network with fixed fusion rules to develop a numeric algorithm based on neyman-pearson criterion. Simulation results are presented to demonstrate the efficiency and convergence properties of the algorithm.

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    APA: Copy

    MIRJALILI, GH., HOSSIENI, H., & SHEYKHI, A.. (2006). OPTIMUM LOCAL DECISION DECISION RULES IN A DISTRIBUTED DETECTION SYSTEM WITH DEPENDENT OBSERVATIONS. ESTEGHLAL, 25(2), 1-10. SID. https://sid.ir/paper/6042/en

    Vancouver: Copy

    MIRJALILI GH., HOSSIENI H., SHEYKHI A.. OPTIMUM LOCAL DECISION DECISION RULES IN A DISTRIBUTED DETECTION SYSTEM WITH DEPENDENT OBSERVATIONS. ESTEGHLAL[Internet]. 2006;25(2):1-10. Available from: https://sid.ir/paper/6042/en

    IEEE: Copy

    GH. MIRJALILI, H. HOSSIENI, and A. SHEYKHI, “OPTIMUM LOCAL DECISION DECISION RULES IN A DISTRIBUTED DETECTION SYSTEM WITH DEPENDENT OBSERVATIONS,” ESTEGHLAL, vol. 25, no. 2, pp. 1–10, 2006, [Online]. Available: https://sid.ir/paper/6042/en

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