淡江大學機構典藏:Item 987654321/98384
English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 64178/96951 (66%)
造訪人次 : 9305901      線上人數 : 230
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
搜尋範圍 查詢小技巧:
  • 您可在西文檢索詞彙前後加上"雙引號",以獲取較精準的檢索結果
  • 若欲以作者姓名搜尋,建議至進階搜尋限定作者欄位,可獲得較完整資料
  • 進階搜尋
    請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/98384


    題名: Effective Neural Network-based Node Localisation Scheme for Wireless Sensor Networks
    作者: Po-Jen Chuang;Yi-Jun Jiang
    貢獻者: 電機工程學系暨研究所
    日期: 2014-01-03
    上傳時間: 2014-07-23 18:12:58 (UTC+8)
    摘要: Wireless sensor networks usually obtain the location of an unknown node by measuring the distance between the
    unknown node and its neighbouring anchors. To enhance both localisation accuracy and localisation success rates, the authors
    introduce a new neural network-based node localisation scheme. The new scheme is distinct because it can make the trained
    network model completely relevant to the topology via online training and correlated topology-trained data and therefore
    attain more efficient application of the neural networks and more accurate inter-node distance estimation. It is also distinct in
    adopting both received signal strength indication and hop counts to estimate the inter-node distances, to improve the distance
    estimation accuracy as well as localisation accuracy at no additional cost. Experimental evaluation is conducted to measure
    the performance of the proposed scheme and other artificial intelligent-based node localisation schemes. The results show
    that, at reasonable cost, the new scheme constantly produces higher localisation success rates and smaller localisation errors
    than other schemes.
    關聯: IET Wireless Sensor Systems 4(2), pp. 97-103
    DOI: 10.1049/iet-wss.2013.0055
    顯示於類別:[電機工程學系暨研究所] 期刊論文

    文件中的檔案:

    檔案 描述 大小格式瀏覽次數
    index.html0KbHTML33檢視/開啟

    在機構典藏中所有的資料項目都受到原著作權保護.

    TAIR相關文章

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - 回饋