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## 必威精装版1.9.0

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### SVD奇异值分解函数学习

2017-08-22 11:31:14| 分类： 默认分类 | 标签： |举报 |字号

SVD Singular value decomposition.
SVD 奇异值分解。
[U,S,V] = SVD(X) produces a diagonal matrix S, of the same dimension as X and with nonnegative diagonal elements in
decreasing order, and unitary matrices U and V so that X = U*S*V'.
[U,S,V] = SVD(X)产生一个对角矩阵S,与X具有相同的维数，具有递减顺序的非负的对角元素，以及酉矩阵U和酉矩阵V满足 X= U*S*V'.
S = SVD(X) returns a vector containing the singular values.

[U,S,V] = SVD(X,0) produces the "economy size" decomposition. If X is m-by-n with m > n, then only the first n columns of U are computed and S is n-by-n. For m <= n, SVD(X,0) is equivalent to SVD(X).
[U,S,V] = SVD(X,0)产生经济型分解。 如果X是m*n，且m>n,那么只有U矩阵的前n列被计算，S是n*n的。

[U,S,V] = SVD(X,'econ') also produces the "economy size" decomposition. If X is m-by-n with m >= n, then it is equivalent to SVD(X,0). For m < n, only the first m columns of V are computed and S is m-by-m.
[U,S,V] = SVD(X,'econ') 也产生 经济型分解。如果X是m*n,且m>=n,那么它等价于SVD(X,0). 对于 m < n，只有V的前m列被计算，S是m*m的矩阵

decreasing order, and unitary matrices U and V so that X = U*S*V'.
[U,S,V] = SVD(X)产生一个对角矩阵S,与X具有相同的维数，具有递减顺序的非负的对角元素，以及酉矩阵U和酉矩阵V满足 X= U*S*V'.
S = SVD(X) returns a vector containing the singular values.

[U,S,V] = SVD(X,0) produces the "economy size" decomposition. If X is m-by-n with m > n, then only the first n columns of U are computed and S is n-by-n. For m <= n, SVD(X,0) is equivalent to SVD(X).
[U,S,V] = SVD(X,0)产生经济型分解。 如果X是m*n，且m>n,那么只有U矩阵的前n列被计算，S是n*n的。

[U,S,V] = SVD(X,'econ') also produces the "economy size" decomposition. If X is m-by-n with m >= n, then it is equivalent to SVD(X,0). For m < n, only the first m columns of V are computed and S is m-by-m.
[U,S,V] = SVD(X,'econ') 也产生 经济型分解。如果X是m*n,且m>=n,那么它等价于SVD(X,0). 对于 m < n，只有V的前m列被计算，S是m*m的矩阵
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