On Wed, May 20, 2009 at 14:46, dmitrey wrote:
> On May 20, 10:34 pm, Robert Kern wrote:
>> On Wed, May 20, 2009 at 14:24, dmitrey wrote:
>> > hi all,
>>
>> > suppose I have A that is numpy ndarray of floats, with shape n x n.
>>
>> > I want to obtain dot(A, b), b is vector of length n and norm(b
On May 20, 10:34 pm, Robert Kern wrote:
> On Wed, May 20, 2009 at 14:24, dmitrey wrote:
> > hi all,
>
> > suppose I have A that is numpy ndarray of floats, with shape n x n.
>
> > I want to obtain dot(A, b), b is vector of length n and norm(b)=1, but
> > instead of exact multiplication I want to
On Wed, May 20, 2009 at 14:24, dmitrey wrote:
> hi all,
>
> suppose I have A that is numpy ndarray of floats, with shape n x n.
>
> I want to obtain dot(A, b), b is vector of length n and norm(b)=1, but
> instead of exact multiplication I want to approximate b as a vector
> [+/- 2^m0, ± 2^m1, ± 2^
hi all,
suppose I have A that is numpy ndarray of floats, with shape n x n.
I want to obtain dot(A, b), b is vector of length n and norm(b)=1, but
instead of exact multiplication I want to approximate b as a vector
[+/- 2^m0, ± 2^m1, ± 2^m2 ,,, ± 2^m_n], m_i are integers, and then
invoke left_shi
