Intrinsic Dimension and Entropy Estimation in Manifold Learnig

Jose A. Costa and Alfred O. Hero

Matab scripts for intrinsic dimension and entropy estimation using k-nearest neighbor graphs. The details of the algorithms can be found in:

J. A. Costa and A. O Hero, "Entropic Graphs for Manifold Learning",
Proc. of IEEE Asilomar Conf. on Signals, Systems, and Computers, Pacific Groove, CA, November, 2003. (.pdf)

J. A. Costa and A. O. Hero, "Geodesic Entropic Graphs for Dimension and Entropy Estimation in Manifold Learning",
to appear in IEEE Trans. on Signal Processing, August, 2004. (.pdf)

Published reports of research using the code provided here (or a modified version) should cite the two articles referenced above.

Comments and questions are welcome. We would also appreciate hearing about how you used this code, improvements made to it, etc. You are free to modify the code, as long as you reference the original contributors.

Download the Matlab package (.zip file). The scripts have minor comments and the readme.txt file contains a description of the files.

Contact jcosta "at" umich "dot" edu for questions or comments.

Last updated May, 2004