Dimitri Pourbaix a écrit :
> Bruce,
>
>>
>> The 2.1 API docs for the Singular Value Decomposition say:
>>
>> The size p depends on the chosen algorithm:
>>
>> for full SVD, p is n,
>> for compact SVD, p is the rank r of the matrix (i. e. the number of
>> positive singular values),
>> for truncated
Bruce,
The 2.1 API docs for the Singular Value Decomposition say:
The size p depends on the chosen algorithm:
for full SVD, p is n,
for compact SVD, p is the rank r of the matrix (i. e. the number of
positive singular values),
for truncated SVD p is min(r, t) where t is user-specified.
but
Bruce A Johnson a écrit :
> The 2.1 API docs for the Singular Value Decomposition say:
>
> The size p depends on the chosen algorithm:
>
> for full SVD, p is n,
> for compact SVD, p is the rank r of the matrix (i. e. the number of
> positive singular values),
> for truncated SVD p is min(r, t) wh
The 2.1 API docs for the Singular Value Decomposition say:
The size p depends on the chosen algorithm:
for full SVD, p is n,
for compact SVD, p is the rank r of the matrix (i. e. the number of
positive singular values),
for truncated SVD p is min(r, t) where t is user-specified.
but I don't se
