This bugzilla service is closed. All entries have been migrated to

Bug 60

Summary: Decompositions - kernel for given dimension
Product: Eigen Reporter: Benoit Jacob <jacob.benoit.1>
Component: GeneralAssignee: Nobody <eigen.nobody>
Status: CONFIRMED ---    
Severity: Feature Request CC: chtz, gael.guennebaud, jacob.benoit.1
Priority: Normal    
Version: unspecified   
Hardware: All   
OS: All   
Bug Depends on: 593    
Bug Blocks: 1608    

Description Benoit Jacob 2010-10-16 04:42:37 UTC
n all rank-revealing decompositions, it would be nice to have a function to construct the kernel matrix for a prescribed dimension of the kernel. At the very least for SVD decompositions, where this would just be taking the n singular vectors associated to the n smallest singular values. In real-world use cases, this is the most useful way to get the kernel. The same idea should then be applied to image() for good measure. 

Then again, with the new SVD that we've been discussing, we'd get that for free (computation/application of U and V on demand).
Comment 1 Christoph Hertzberg 2014-06-20 11:02:30 UTC
Bug 593 is related and should be solved to make this useful.
Comment 2 Nobody 2019-12-04 09:42:02 UTC
-- GitLab Migration Automatic Message --

This bug has been migrated to's GitLab instance and has been closed from further activity.

You can subscribe and participate further through the new bug through this link to our GitLab instance: