English  |  正體中文  |  简体中文  |  全文筆數/總筆數 : 6507/11669
造訪人次 : 29716398      線上人數 : 456
RC Version 3.2 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
搜尋範圍 進階搜尋

請使用永久網址來引用或連結此文件: http://ir.ncue.edu.tw/ir/handle/987654321/11780

題名: Applying Neural Network Algorithm to Data Association Technique
作者: Chung, Yi-Nung;Chen, H.-T.;Juang, D.-J.;Chen, J.-Y.;Lee, J.-R.
貢獻者: 電機工程學系
關鍵詞: Data association;Competitive Hopfield neural network;Kalman filter
日期: 2005-05
上傳時間: 2012-07-02T02:08:27Z
出版者: IEEE
摘要: Data association plays an important role in radar tracking algorithm .The problem of tracking multiple targets is studied in this paper. In order to solve the complicated situation and reduce computation burden because of the multiple tracking environment, an approach has been developed in this paper. This algorithm is implemented with an adaptive filter which consists of a data association technique denoted competitive Hopfield
neural network and Kalman filtering to solve both data association and target tracking problems simultaneously. In order to prove the tracking performance, a computer simulation algorithm is proposed in this paper. Because of its computation capability of this algorithm, the radar measurement related to existed target tracks can be chosen optimally. Computer simulation results indicate that this approach
successfully and optimally solves the data association problems.
關聯: IEEE CNNA, 2005年5月28-30日: 114-117
顯示於類別:[電機工程學系] 會議論文

文件中的檔案:

檔案 大小格式瀏覽次數
index.html0KbHTML602檢視/開啟


在NCUEIR中所有的資料項目都受到原著作權保護.

 


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