Re: [eigen] HELP : SVD too slow |

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*To*: eigen@xxxxxxxxxxxxxxxxxxx*Subject*: Re: [eigen] HELP : SVD too slow*From*: Helmut Jarausch <jarausch@xxxxxxxxxxxxxxxxxxx>*Date*: Fri, 29 Jun 2012 11:30:49 +0200

On 06/29/2012 10:29:06 AM, Gaurav Gupta wrote:

The maximum dimension is 8 x 6, if bordered matrix approach canimprovespeed, I am very much interested

If the rank defect is about 1 or 2, bordered system could be a speed up. For a first impression you might have a look at

IMA J. Numer. Anal. 13 (1993), pp 161-180 or chapter 3 in http://books.google.de/books?id=I1M5ZISH9SsC&pg=PA350&lpg=PA350&dq=Govaerts+Mixed+block+elimination+for+linear+systems+with+wider+borders+IMA+J+Numer.+Anal.&source=bl&ots=ddaG3Oecid&sig=IqMi-Gth07WFxM5iOp8Rflz9awQ&hl=de&sa=X&ei=tWztT-aPFYjm4QS34uzuDQ&sqi=2&ved=0CEYQ6AEwAg#v=onepage&q=Govaerts%20Mixed%20block%20elimination%20for%20linear%20systems%20with%20wider%20borders%20IMA%20J%20Numer.%20Anal.&f=false FORTRAN software is here http://www.netlib.org/linalg/bemw.tgz If you like I can send you my Scilab application which tries to find a parameter-dependend matrix of prescribed rank (defect). Helmut.

On Fri, Jun 29, 2012 at 1:55 PM, Helmut Jarausch < jarausch@xxxxxxxxxxxxxxxxxxx> wrote: > On 06/29/2012 10:21:25 AM, Gaurav Gupta wrote: >>> I opted for eigen3 to improve speed of my program than on MATLAB,but it>> is >> taking more time than MATLAB.>> I am using JacobiSVD for calculating nullspace, which is takingmost of>> the >> time, any suggestions for improving speed, >> or any way to implement SVD faster. >> >> > > What dimension will the nullspace have? >> If not too large you could consider using a bordered matrixapproach.> If you're interested I'll be happy to give to some references aneven a> Scilab implementation > of this. > > Helmut. > > >

**References**:**Re: [eigen] HELP : SVD too slow***From:*Gaurav Gupta

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