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研究生:蔡秉達
論文名稱:無線感測網路中利用決策回授與基於證據理論局部融合之分散式估計方法
論文名稱(外文):Distributed Estimation Schemes with Decision Feedback and Evidence Theory-based Local Fusion for Wireless Sensor Networks
指導教授:蔡育仁蔡育仁引用關係
學位類別:碩士
校院名稱:國立清華大學
系所名稱:通訊工程研究所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2014
畢業學年度:102
語文別:中文
論文頁數:48
中文關鍵詞:無線感測網路感測元件融合中心證據理論預測能源消耗
相關次數:
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無線感測網路近來因為其體積小、成本低且元件之間是以無線通訊的方式,更可省下布置網路的費用,而受到軍事工業及民間研究機構的愛戴。在目前舉凡在軍事、生態及醫學等眾多研究當中,隨處可見其在研究當中所扮演腳色的重要性與日俱增。
無線感測網路的架構,是透過感測元件觀察其周圍環境,並將觀察結果交由融合中心整合,進而讓使用者得到環境中的訊息。在這篇我們使用合作式資訊聚合的方式,將每個感測元件自身在環境中所感測到的觀察,利用多位元量化的方式,並只允許其感測元件序列式地傳送一個位元給融合中心,藉由我們所設計的由感測元件的位元序列式投票的硬決策估計出未知的參數,除了可以節省頻寬的消耗,也可節省感測元件的能源。
除此之外,我們設計一藉由融合中心在每決策出前一個位元時,把決策結果告知環境中所有的感測元件,透過證據理論上的應用,利用可靠的結合規則,將決策結果與感測元件自身的觀察,在感測元件上做出下一個位元的決策並回傳給融合中心,藉此除了改善更多的能源的消耗,並同時提昇對未知參數估計的表現。

中文摘要
ABSTRACT
誌謝
CONTENTS
LIST OF FIGURES AND TABLES
Chapter 1 Introduction
Chapter 2 Cooperative Information Aggregation (CIA) Schemes for Distributed Estimation in Wireless Sensor Networks
2.1 System Model of CIAS
2.2 System Model of CIA with Decision Feedback based D-S Theory
2.3 CIAS and CIA with Decision Feedback based D-S Theory Estimation Scheme
Chapter 3 CIAS with Decision Feedback Based D-S Theory
3.1 D-S Theory
3.2 D-S Theory in CIAS System with Decision Feedback
3.3 Reliable D-S theory Combination Rule
3.4 Schemes on CIAS with Decision Feedback by using D-S Theory
Chapter 4 Analysis on the Proposed Schemes
4.1 Node Accuracy Rate and Decision Accuracy Rate
4.2 Difference Schemes of Node Accuracy Rate and Decision Accuracy Rate
Chapter 5 Simulation Results and Discussion
5.1 Energy Saving
5.2 Estimation Performance
Chapter 6 Conclusion
REFERENCES

[1] Y. Li, M. T. Thai, and W. Wu, Wireless Sensor Networks and Applications, Springer, 2008, pp.331–347.
[2] K. Sohraby, D. Minoli, and T. Znati, Wireless Sensor Networks: Technology, Protocols, and Applications, John Wiley & Sons, Hoboken, New Jersey, 2007.
[3] R. Madan, S. Cui, S. Lall, and A. Goldsmith, “Cross-Layer Design for Lifetime Maximization in Interference-Limited Wireless Sensor Networks,” IEEE Trans. Wireless Commun., vol. 5, no. 11, pp. 3142–3152, Nov. 2006.
[4] R. Madan, S. Cui, S. Lall, and A. Goldsmith, “Modeling and optimization of transmission schemes in energy-constrained wireless sensor networks,” IEEE/ACM Trans. Networking, vol. 15, no. 6, pp. 1359–1372, 2007.
[5] I. Akyildiz, W. Su, Y. Sankarsubramaniam, and E. Cayirci, “Wireless sensor networks: A survey,” Comput. Netw., vol. 38, pp. 393–422, Mar. 2002.
[6] Cheng-Ju Chang, Yuh-Ren Tsai, “Cooperative Information Aggregation Based Distributed Sequential Estimation in Wireless Sensor Networks,” 2011.
[7] G. Shafer, “A Mathematical Theory of Evidence,” Princeton, NJ: Princeton Univ. Press, 1976.
[8] T.Denoeux, ”A Neural Network Classifier Based on Dempster-Shafer Theory,” IEEE Trans. on System, Man and Cybernetics, vol.30, no.2, pp.131-150, Mar.2000.
[9] B.V.Dasarathy, ”Decision Fusion Strategies in Multi-sensor Environments,” IEEE Trans. on System, Man and Cybernetics, vol.21, no.5, pp.1140-1154, Sep/Oct. 1991.
[10] Hongwei Zhu, Basir O., and Karray F., ”Data Fusion for Pattern Classification via the Dempster-Shafer Evidence Theory,” IEEE International Conference on Systems, Man and Cybernetics, vol.7, Oct. 2002.
[11] Huadong Wu, Siegel, M., Stiefelhagen, R., and Jie Yang, “Sensor Fusion Using Dempster-Shafer Theory,” IEEE Instrumentation and Measurement Technology Conference, Vol.1 7-12, May 2002.
[12] J. Li and G. AlRegib, “Rate-constrained distributed estimation in wireless sensor networks,” IEEE Trans. Signal Process., vol. 55, no. 5, pp. 1634–1643, May 2007.
[13] Z.-Q. Luo and J.-J. Xiao, “Decentralized estimation in an inhomogeneous sensing environment,” IEEE Trans. Inf. Theory, vol. 51, no. 10, pp. 3564–3575, Oct. 2005.
[14] F. Gray, “Pulse code communication,” U.S. patent no. 2,632,058, March 17, 1953.
[15] Z. Wentao, F. Tao, and J. Yan, ”Data fusion using improved Dempster-Shafter evidence theory for vehicle detection,” in Proc. 4th Int. Conf. Fuzzy Syst. Knowl. Discov., Aug. 2007, vol1. 1, pp.487-491.
[16] Ping Wang, “The Reliable Combination Rule of Evidence in Dempster-Shafer Theory,” IEEE, 2008.

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