表現極為正直 的英文怎麼說

中文拼音 [biǎoxiànjíwéizhēngzhí]
表現極為正直 英文
behave with scrupulous honesty
  • 表 : Ⅰ名詞1 （外面;外表） outside; surface; external 2 （中表親戚） the relationship between the child...
  • 現 : Ⅰ名詞1 （現在; 此刻） present; now; current; existing 2 （現款） cash; ready money Ⅱ副詞（臨時; ...
  • 極 : i 名詞1 （頂點; 盡頭） the utmost point; extreme 2 （地球的南北兩端; 磁體的兩端; 電源或電器上電流...
  • 正 : 正名詞（正月） the first month of the lunar year; the first moon
  • 直 : Ⅰ形容詞1 （成直線的; 硬挺的） straight; stiff 2 （跟地面垂直的; 從上到下的; 從前到后的） erect; v...
  • 表現 : 1 （所顯露的行為或作風等） expression; representation; manifestation; show; behaviour; conduct 2 ...
  • 極為 : awful
  • 正直 : honest; upright; fair-minded
  1. Most current algorithms only work well in special conditions, because of the abnormity of signals in the real world. now, the research in the ica arises much passion and the ica has brought about many applications. the primary results the writer has got are as the following : after a whiting process, it is a key to find an orthogonal matrix to throw away the high - order redundant information between components

    由於現實生活中信號十分不規則，目前提出的演算法大多隻能針對某類信號分離，鑒于目前在ica方面極大的研究熱情和強大的背景支持，作者對ica離線演算法做了一定研究，主要內容和工作包括如下: ica問題經過白化處理后，尋找去除高階相關的正交矩陣成為問題關鍵，而正交矩陣具有特殊的空間結構，組成它的每個列向量可視作rn中單位超球表面上一點，當這些點彼此垂直時，整體就組成一個正交矩陣。
  2. To the problem that finding rules in enormous data is very time - consumable and the expansibility of existed algorithms is not very good, the thesis proposes a new method to discompose large data table based on the concepts of positive region and the importance of attribute in rough set theory. existed algorithms of rule deduction can be applied directly on the tree structure obtained by partition and the times for computation will be reduced observably. validation of information entropy on the partition structure shows that the partition of data table will not lead to the loss of information, while the computing speed increases at the same time, which reflects the practicability and rationality about the partition of large data table

    針對海量數據處理起來極為耗時，現有演算法拓展性較差的問題，基於rough集理論中的集合正域概念以及由此定義的屬性重要性概念，提出一種大型數據表分解演算法，現有的規則歸納演算法可直接在分解得到的樹型結構上應用，將大大降低知識發現的時間，並從信息理論的角度利用信息熵概念對該分解結構進行了驗證，分析了這種分解的實用性及合理性，揭示了這種分解結構在提高計算速度的同時不會損失信息量。
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