Python库numpy中的svd分解和Matlab中的svd的一点区别

下面是两个测试，同样的数据，不同的版本，请诸君仔细看来：

1.Matlab版SVD分解

H = [3.16991321031250,52.4425641326457,2.73475152482102;-8.76695007100685,43.4831885343255,-37.1705395356264;-1.59218748085971,-24.3510937156625,12.8339630267640];

[U,S,V] = svd(H);

 得出来的结果

U =
    0.6124    0.7695   -0.1814
    0.7073   -0.6357   -0.3091
   -0.3531    0.0610   -0.9336

V =
   -0.0479    0.2651    0.9630
    0.9249    0.3759   -0.0575
   -0.3772    0.8880   -0.2631
S =
   77.2740         0         0
         0   29.8639         0
         0         0    3.7601

2.Python版SVD分解

from numpy import *

def test():
    Base = array([[1.92028349427775,0.938200267748656,8.61139811393332,6.71431139674026,3.47712671277525,2.62145317727807,2.42785357820962,3.59228210401861],[1.38874202829155,5.25404403859336,4.84853333552102,7.