(3.238.249.17) 您好!臺灣時間:2021/04/13 19:18
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果

詳目顯示:::

我願授權國圖
: 
twitterline
研究生:魏逢毅
研究生(外文):Fong-Yi Wei
論文名稱:多輸入多輸出之l1最佳化解迴旋濾波器
論文名稱(外文):Deconvolution Filter Design in MIMO System via l1 Optimization: LMI Approach
指導教授:陳博現
指導教授(外文):Bor-Sen Chen
學位類別:碩士
校院名稱:國立清華大學
系所名稱:電機工程學系
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:2003
畢業學年度:91
語文別:中文
論文頁數:32
中文關鍵詞:多輸入多輸出系統等化解迴旋濾波器線性矩陣不等式方法
外文關鍵詞:MIMO systemequalizationDeconvolution filterLMI approach
相關次數:
  • 被引用被引用:0
  • 點閱點閱:116
  • 評分評分:系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔系統版面圖檔
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
在多輸入多輸出的信號傳輸系統中,存在著未知但持續有界的雜訊,並且由於多輸入多輸出通道的影嚮,我們提出了一個l1次最佳解迴旋的濾波器來重建由信號源所輸入的訊號。這個l1最佳化的解迴旋濾波器的主要設計原理是要最小化重建訊號與原始傳輸訊號之與的誤差鋒值。首先建立這個問題的模型和公式化這個所要處理的問題,使用的是狀態空間的矩陣方法,並且利用這個方法,將這個問題加以簡化。這個l1最佳化解迴旋濾波器設計問題藉由用線性矩陣不等式極小化l1基準的上界來轉型成l1次最佳化的解迴旋濾波器設計問題。在轉型之後,原本非常複雜的多輸入多輸出 解迴旋濾波器設計就可以很容易的由凸面最佳化線性矩陣不等式解出,而在解出之後,即可以設計出此濾波器,此濾波器有強健性的特性,所以也可以做為通訊系統抗干擾之用,因此,在這個方面,有著比傳統的等化器更好的效果。為了要改善所提出的l1解迴旋濾波器的暫態嚮應,我們也討論了附有極點佈置的l1次最佳化解迴旋濾波器,藉由這個設計,如果系統需要暫態的效能,則可以依自己的需求加入不等式之中,所以這個設計是非常有彈性的。另外,為了強健性的需求,文章中也考慮了混合l1與H2基準的解迴旋濾波器。而在理論設計完之後,許多模擬也加入了這篇論文之中,藉由這些模擬,我們的設計得以得到佐證,也可以從這些模擬之中,看出我們所提出的濾波器的好處及優點所在。

A l₁ suboptimal deconvolution filter is proposed for multi-input multi-output (MIMO) signal transmission systems with unknown but persistently bounded noises. The l₁ optimal deconvolution filter is to reconstruct the transmitter signal such that the peak of reconstruction error due to the noises is as small as possible. The l₁ optimal deconvolution filter design problem is transformed to suboptimal deconvolution filter problem by minimizing the upper bound of l₁ norm with some linear matrix inequality (LMI) constraints. In this situation, the very complicate l₁ optimal deconvolution filter design problem in MIMO systems can be easily solved by LMI method via convex optimization technique. In order to improve the transient response of l₁ deconvolution filter, the suboptimal l₁ filter with desired pole placement is also discussed. Further the mixed l₁/H₂ deconvolution filter is considered for performance robustness.

目錄 …………………………………………………………………… i
摘要 ………………………………………………………………… ii
第一章:簡介………………………………………………………… iii
第二章:模型建立和問題描述……………………………………… iv
第三章:次佳 解迴旋濾波器的設計……………………………… v
第四章:次佳 解迴旋濾波器的設計……………………………… vi
第五章:電腦模擬結果與討論……………………………………… vii
第六章:結論……………………………………………………… viii

1 : J.M. Mendel "White noise estimator for seismic data processing in oil exploration," IEEE Trans. Automat. Contr. vol. AC-22, pp. 694-706, 1977
2 : C.Y. Chi and J.M. Mendel, "Performance of minimum-variance deconvolution filter," IEEE Trans. Acoust Speech, Signal Processing, vol. 133, pp. 13-18, 1986
3 : L. Chisci and E. Mosca, "A general polynomial solution to MMSE deconvolution problem," IEEE Trans. Acoust. Speech, Signal Processing, vol. 39, pp. 962-965, 1991
4 : B.S. Chen and S.C. Peng, "Optimal deconvolution filter design based on orthogonal principle," IEEE Trans. Signal Processing, vol. 25, pp. 316-372, 1991
5 : S. Verdu and H.V. Poor, "On minimax robustness: A general approach and applications," IEEE Trans, Inform. Theory, vol. IT-30, pp. 328-340, 1984
6 : M.J. Grimble and A.E. Sayed, "Solution of H_{∞} optimal linear filtering problem for discrete-time systems," IEEE Trans. Acoust. Speech, Signal Processing, vol. 38, pp. 1092-1104, 1990
7 : T. Chen and Bruce A. Francis, "Design of multirate filter banks by H_{∞} Optimization." IEEE Trans. Signal Processing, vol. 43, No. 12, Dec. 1995
8 : A.T. Erdogan ; Hassibi, B.; Kailath, T.; "On Linear H_{∞} Equalization of communication channels"Signal Processing," IEEE Transactions on Signal processing, vol. 48 no. 11 pp. 3227 -3231, 2000
9 : A.T. Erdogan ; Hassibi, B.; Kailath, T.; "FIR H_{∞} equalization" IEEE Trans., Acoustics, Speech, Signal Processing, vol: 5, 2000, pp. 2729 -2732
10 : M.J. Grimble and A.E. Sayed "Solution of H_{∞} optimal linear filter problem for discrete-time systems" IEEE Trans. Acoust Speech Signal processing, vol. 38, pp.1092-1104, 1990
11 : B. Hassibi, A. H. Sayed, and T. Kailath Indefinite Quadratic Estimation and Control: A Unified Approach to H₂ and H_{∞} Theories. SIAM Studies in Applied Mathematics, New York, 1998
12 : J.B. Bednar, B.R. Yarlagadda, and T. Watt, "ℓ₁ deconvolution and its application to seismic signal processing," IEEE Trans. Acoust Speech, Signal Processing, vol. ASSP-34, pp. 1655-1658, 1986
13 : M.A. Mendovittz, "ℓ₁-optimal estimation for discrete-time linear systems," IEEE Trans. Signal Processing, vol. 41, pp. , 1993
14 : S.C. Peng and B.S. Chen, "Deconvolution filter design via ℓ₁ optimization technique," IEEE Trans. Signal Processing, vol. 45, no.3, pp. 736-746 1997
15 : M. Chilali and P. Gahinet, "H_{∞} design with pole placement constraints: An LMI approach," IEEE Trans. Automat. Contr., pp.358-367, 1996
16 : A. Graham, Kronecker Product and Matrix Calculus with Aplications. Chichester, U.K.: Ellis Horwood, 1981
17 : Y.Li and K.J.R. Liu "Adaptive blind source separation and equalization for multiple-input/multiple-output systems," IEEE Trans. Information Thoery, vol. 44, pp. 2864-2876, Nov.1998
18 : N. Al-Dhahir and A. H. Sayed, "The finite-length multi-input multi-output MMSE-DFE," IEEE Trans. Signal Processing, vol. 48, pp. 2921-2936, Oct. 2000
19 : C. Komninakis, C. Fragouli, A.L. Sayed and R.D. Werel. "Multi-input multi-output fading channel tracking and equalization using kalman filtering," IEEE Trans. Signal Processing, vol. 50 No. 5, pp. 1065-1076, May 2002
20 : W. Hachem, F. Desbouvries, and P. Loubaton, "MIMO channel blind identification in the presence of spatially correlated noise," IEEE Trans. Signal Processing, vol. 50, No. 3, pp. 651-661, Mar. 2002
21 : L. Tong and S. Perreau, "Multichannel blind idenfication: from subspace to maximum likelihood methods," in Proc. IEEE, vol. 86, pp.1951-1968, Oct. 1998
22 : R.E. Skelton, T. Iwasaki and K. Grigoriadis. A Unified Algebraic Approach to Linear Control Design. Taylor&Francis 1998
23 : S. Verdu, "Minimum probability of error for asynchronous Gaussian multiple-access channels," IEEE Trans. Inform. Theory, vol 42, pp. 85-96, Jan. 1996
24 : B.S. Chen, C.W. Lin and Y.L. Chen, "Optimal signal reconstruction in noisy filter bank systems: multirate kalman synthesis filtering approach," IEEE Trans. Signal Processing, vol. 43 No. 11, pp. 2496-2504, Nov. 1995
25 : L. Shengping; "Mixed l₁/H₂ control for MIMO systems," IEEE Trans. Intelligent Control and Automation vol. 1 pp. 268 -272, June 2002
26 : A. Casavola and D. Famularo; "Q domain sub/super-optimization linear programming methods for MIMO l₁ control problems," IEEE Trans. Decision and Control, vol. 1, pp. 617-622, Dec. 2000
27 : M. Sznaier and B. Juanyu, "Mixed l₁/H_{∞} control of MIMO systems via convex optimization," IEEE Trans. Automatic Control , vol. 43, pp. 1229-1241, Sept. 1998
28 : Matlab Toolbox
29 : I. Yaesh, and U. Shaked, "A transfer function approach to the problems of discrete-time system: H_{∞} optimal linear control and filtering," IEEE Trans. Automat. Contr.., vol. AC-36, pp. 1264-1271, no. 11, Nov. 1991
30 : S. Boyd, L. El Ghaoui, E. Feron, and V. Balakrishrnan, Linear Matrix Inequalities in Systems and Control Theory, vol. 15 Philadelphia: SIAM, 1994

QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top
系統版面圖檔 系統版面圖檔