ADAPTIVE DECISION FUSION IN DETECTION NETWORKS

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MIRJALILI GH.; AREF MOHAMMAD REZA; NAYEBI M.M.; KAHRIZI MASOUD

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Journal: ESTEGHLAL Year:2000 | Volume:19 | Issue:1 Page(s): 1-14

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Title

ADAPTIVE DECISION FUSION IN DETECTION NETWORKS

Author(s)

MIRJALILI GH. | AREF MOHAMMAD REZA | NAYEBI M.M. | KAHRIZI MASOUD | Issue Writer Certificate

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Abstract

In a detection network, the final decision is made by fusing the decisions from local detectors.The objective of that decision is to minimize the final error probability. To implement an optimal fusion rule, the performance of each detector, i.e. its probability of false alarm and its probability of missed detection as well as the a priori probabilities of the hypotheses, must be known. However, these statistics are usually unknown or may vary with time. In this paper, we develop a recursive algorithm that adapts the fusion center.This approach is based on the time-averaging of local decisions and on using the analytic solutions that guarantee the asymptotic convergence. Also a simple method is proposed that enables the algorithm to track changes faster. Simulation results are presented to demonstrate the efficiency and convergence properties of the algorithm.

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APA: Copy

MIRJALILI, GH., AREF, MOHAMMAD REZA, NAYEBI, M.M., & KAHRIZI, MASOUD. (2000). ADAPTIVE DECISION FUSION IN DETECTION NETWORKS. ESTEGHLAL, 19(1), 1-14. SID. https://sid.ir/paper/5887/en

Vancouver: Copy

MIRJALILI GH., AREF MOHAMMAD REZA, NAYEBI M.M., KAHRIZI MASOUD. ADAPTIVE DECISION FUSION IN DETECTION NETWORKS. ESTEGHLAL[Internet]. 2000;19(1):1-14. Available from: https://sid.ir/paper/5887/en

IEEE: Copy

GH. MIRJALILI, MOHAMMAD REZA AREF, M.M. NAYEBI, and MASOUD KAHRIZI, “ADAPTIVE DECISION FUSION IN DETECTION NETWORKS,” ESTEGHLAL, vol. 19, no. 1, pp. 1–14, 2000, [Online]. Available: https://sid.ir/paper/5887/en

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