Employing a factorization based on the least significant singular values provides a matrix approximation with many surprisingly useful properties. This Reverse Singular Value Decomposition, RSVD, is also referred to as Subordinate Component Analysis, SCA, to distinguish it from Principal Component Analysis. ... read more >>

High resolution measurements of the depth of the mold for the United States one cent coin provide an interesting data set.... read more >>

ContentsTim DavisSparse Matrix VisualizationsMusic VisualizationsMetastaseisBlue MondayElectrodoodleMorning Has BrokenBach Toccata and FugueNotesArt StudioTim DavisAt the recent SIAM conference on... read more >>

The Tektronix 4081 minicomputer at Argonne National Laboratory in the summers of 1977 and '78 played an important role in the early development of MATLAB.... read more >>

I am surprised when many of the singular values of a nonsymmetric variant of the Hilbert matrix turn out to be nearly equal to $\pi$. The explanation involves the Fourier series for a square wave.... read more >>

Magic Stars are a little like Magic Squares. My grandson was introduced to them in his junior high school math class.... read more >>

The Rosser matrix is a classic matrix eigenvalue test problem.... read more >>