How does `svd(A*A')` reduce the computational cost?
5 Ansichten (letzte 30 Tage)
Ältere Kommentare anzeigen
Computing singular value decomposition is the main computational cost in many algorithms .
For a matrixA(m*n) ,if m is much larger than n , one can compute the SVD of A*A',and then get an approximate SVD of by simple operations to reduce the computational cost.
How does it reduce the computational cost?
2 Kommentare
Antworten (1)
Cutie
am 21 Jun. 2021
SVD reduces computational costs because it provides a numerically stable matrix decomposition. You may refer to https://www.youtube.com/playlist?list=PLMrJAkhIeNNSVjnsviglFoY2nXildDCcv for detailed wokrings of SVD
Siehe auch
Kategorien
Mehr zu Eigenvalues finden Sie in Help Center und File Exchange
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!