Computational Mathematics Laboratory Course AA 2013/14


  • 2014-02-24: Time changed: now the course is on Wednesday 9-11 and Friday 11-13, still in room I.


The main source of (official) information on the course is the Syllabus. Be sure to check it first.

Other material

  • Slides presenting the course, in Italian (adapted from those of Gianna Del Corso, who taught the course until 2012/13). They contain an example application (face recognition through SVD).
  • Detailed lecture information (registro lezioni) on the university website.

Teaching material

  • A sample set of dots to test interpolation algorithms (lecture 1, hopefully)
  • De Casteljau's algorithm in various versions: castel2.m castel2b.m castel2split.m castel3.m
  • Two sample images from the University of Southern California's collection: man1024.tiff peppers512.tiff
  • Sample sparse matrices to test Arnoldi-type algorithms (and beyond):
    • convmat.mat Convolution matrix with psfGauss([5,5],0.5), zero boundary condition, 50x50 image. Condition number approx. 30.
    • convmat2.mat Convolution matrix with psfGauss([5,5],2), zero boundary condition, 50x50 image. Condition number approx. 2e5.
    • karate.mat A classical example in network theory: 1977 Zachary's "karate club" experiment (undirected friendship graph between members of a Karate club, very small scale)
  • Test images for face classification (from the Yale face database)
  • Quick notes for the lecture on numerable-states queuing models (QBD processes).