rank factorization 中文意思是什麼
rank factorization
解釋
秩分解- rank : n 1 列，排；【軍事】行列；〈pl 〉陣線，隊伍，軍隊；〈pl 〉士兵，列兵。2 階層，等級，地位；身份；...
- factorization : 分解為因子
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The concept of row ( column ) transposed matrix and row ( column ) symmetric matrix is given, their basic property is studied, and the formula for full rank factorization and orthogonal diagonal factorization of row ( column ) symmetric matrix are presented, which can reduce dramatically the amount of calculation and save the cpu time and memory without loss of any numerical precision
摘要提出了行（列）轉置矩陣與行（列）對稱矩陣的概念，研究了其性質，給出了行（列）對稱矩陣的滿秩分解和正交時角分解公式，極大地減少了行（列）對稱矩陣的滿秩分解和正交對角分解的計算量與存儲量，且沒有降低數值精度。 -
Different from other rank reduction methods, such as pca ( principal component analysis ) and vq ( vector quantization ), nmf ( nonnegative matrix factorization ) can get nonnegative, sparse basis vectors which make possible of the concept of a parts - based representation
與pca （主分量分析）和vq （矢量量化）等降維演算法不同， nmf （非負矩陣分解）演算法能夠分解出非負的，稀疏的特徵矩陣和編碼矩陣，能夠提取原始數據向量的局部特徵，使基於局部特徵進行分類的聚類演算法更容易實現。 -
In this thesis, we mainly use snmf ( sparse nonnegative matrix factorization ) as the method of rank reduction, which extend the nmf to include the option to control sparseness explicitly
本文主要採用snmf （非負稀疏矩陣分解）演算法作為降維和提取特徵向量的工具，該演算法是在nmf演算法的基礎上加上顯式地稀疏因子控制而形成的一種非負矩陣分解方法。
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