invariant subspace 中文意思是什麼
invariant subspace
解釋
不變子空間-
Firstly, a new joint filterbank precoders and decision feedback equalizers structure is proposed, and the corresponding optimization result based on the maximal mutual information criterion is derived. secondly, the concept of dt canonical model is proposed, which is very suitable for the task of blind signal processing based on the second - order statistical of the observations. thirdly, the methods of blind equalization and identification of the tv dispersive channels are researched systematically based on the proposed dt canonical model, and a subspace blind identification algorithm of the time - invariant channel matrix is developed
本文創新性的成果在於：提出了預編碼-判決反饋聯合均衡系統結構，並從理論推導得出了對應的最大互信息量最優化設計結果；首次提出了時變色散通道的離散正則模型概念，該模型適宜於利用觀察數據的二階統計量進行盲信號處理；基於離散正則模型對時變色散通道進行了系統的盲均衡和盲辨識方法研究，提出了對時不變通道矩陣的子空間盲辨識演算法；針對誤差傳播效應問題，提出了可以消除誤差傳播效應的兩級盲辨識演算法；提出了基於離散正則模型的直接盲均衡演算法；提出了基於特徵恢復思想的神經網路直接自適應盲均衡演算法。 -
In this paper, we discuss a new class of m - paranormal operators and give the properties of these operators. further, we also give an existence condition of the invariant subspace
討論了一個新的運算元類: m -仿正規運算元.給出了這一類運算元的部分性質及不變子空間存在的條件 -
In the third chapter, the perturbation of invariant subspace, singular subspaces and deflating subspaces are discussed
第三章討論了不變子空間、奇異子空間對和收縮子空間對的擾動。 -
Numerical result shows that the new method is more efficient in convergence than the standard lanczos algorithm ; the second algorithm generalizes the implicitly restarted arnoldi ( ira ) augmented by soreesen to the implicitly restarted lanczos algorithm, which improves the convergence rate of lanczos algorithm by making good use of the spectral information obtained from the previous process. the last algorithm utilizes deflation strategies to the second algorithm to forming invariant subspace for a, so that the stability can be kept in computing process
數值試驗表明，該演算法比標準lanczos方法具有更好的收斂性；第二種演算法是將求解特徵值問題的隱式循環arnoldi方法（ ira ）應用於求解對稱不定線性方程組的lanczos演算法，充分利用lanczos演算法過程中的譜信息，確定預處理；第三種演算法是在第二種演算法的基礎上，運用收縮技巧，形成近似不變子空間，以提高收斂速度和數值穩定性。
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