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1)  leading dimension
矩阵主维
1.
With the development of computer architecture and the introduction of cache, blocking has been the main method to optimize performance in matrix computing, and the effect of leading dimension becomes important to blocking algorithms performance.
随着计算机体系结构的发展,高速缓存(cache)的引入,分块方法成为矩阵计算中性能优化的主要方法,而矩阵主维对分块算法的性能影响很大。
2)  matrix host computer
矩阵主机
3)  principal submatrix
主子矩阵
1.
The well-known matrix inequality (AB)~(-1)≤A~(-1)B~(-1) involving Hadamard product of positive definite matrices is refined to(AB)~(-1)≤diag((A~(-1)(α)~(-1)B(α))~(-1),(A(α′)B~(-1)(α′)~(-1))~(-1)),≤diag(A~(-1)(α)B(α)~(-1),A(α′)~(-1)B~(-1)(α′))≤A~(-1)B~(-1),where A(α) is the leading principal submatrix and α′ is the complementary sequence of α.
周知的正定矩阵A和B的Hadamard乘积矩阵不等式 :(A B) -1 ≤A-1 B-1 被精细为(A B) -1 ≤diag((A-1 (α) -1 B(α) ) -1 ,(A(α′) B-1 (α′) -1 ) -1 ) ,≤diag(A-1 (α) B(α) -1 ,A(α′) -1 B-1 (α′) )≤A-1 B-1 ,这里A(α)是A的主子矩阵且α′是α的补序列 ;同时给出了这些不等式的等式成立的充分必要条
4)  main matrix
主矩阵
5)  principal matrix solution
主矩阵解
6)  dominant color matrix
主色矩阵
1.
To express accurately the information of color distributing of an image,in this paper,two new color feature of color-based image retrieval method are proposed,which are dominant color matrix and dominant color pair matrix.
提出将描述图像中颜色分布信息的主色矩阵和主色对矩阵作为图像的检索特征。
补充资料:主维
1.犹言作主。
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