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標題: Wireless Sensor Networks（共96頁pdf下載） [打印本頁]

作者: jbrzan 時間: 2018-4-9 14:11
標題: Wireless Sensor Networks（共96頁pdf下載）
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1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.1 Motivation of Distributed Consensus Estimation . . . . . . . . . . . . . . . . . 1
1.2 Overview of Distributed Consensus Estimation . . . . . . . . . . . . . . . . . . 3
1.3 Distributed Observation and Consensus Strategy. . . . . . . . . . . . . . . . . 3
1.3.1 Observation-Only Consensus . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3.2 Observation+Innovation Consensus Strategy . . . . . . . . . . . . . 4
2 Distributed Consensus Estimation ofWireless Sensor Networks . . . . . 5
2.1 Consensus Based Distributed Parameter Estimation . . . . . . . . . . . . . . 5
2.1.1 Average Consensus . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.1.2 In-Network Regression Consensus . . . . . . . . . . . . . . . . . . . . . . 8
2.1.3 Observation+Innovation Consensus . . . . . . . . . . . . . . . . . . . . . 9
2.2 Consensus Based Distributed Tracking . . . . . . . . . . . . . . . . . . . . . . . . . 10
3 Consensus-Based Distributed Parameter Estimation
with Asymmetric Communications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
3.2 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.2.1 Network Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
3.2.2 Concepts From Graph Theory . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.2.3 Distributed Consensus-Based Unbiased Estimation
Algorithm: Algorithm DCUE . . . . . . . . . . . . . . . . . . . . . . . . . . 16
3.3 Characterization of RNs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3.3.1 Non-cyclic Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
3.3.2 Cyclic Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
3.3.3 Markov Chain Based Characterization . . . . . . . . . . . . . . . . . . . 22
3.3.4 Computing γ˜ij for Steiner-Tree-Based RN Placement . . . . . . 24
3.4 Convergence Analysis: Asymptotic Unbiasedness and Consistency 25
3.4.1 Asymptotic Unbiasedness of the DCUE Algorithm . . . . . . . . 26
3.4.2 Consistency of the DCUE Algorithm . . . . . . . . . . . . . . . . . . . . 29

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