GKA
Gaussian Kernel Algorithm Correlation Dimension Estimation
Estimation of correlation dimension, entropy and noise level using the
GKA algorithm.
INSTALLATION
- Place the contents of this archive in a directory on MATLAB's search
path.
- Compile the mex functions. On recent versions of MATLAB,
>> mex interbinref.c
>> mex interbin.c
should be sufficient. Older versions may require you to run mex -setup
first. If you know nothing about mex files, start by reading the help.
- run test.m
USAGE
See individual help files and example in test.m
DISTRIBUTION
Please do not redistribute these programs without my permission. This
distribution can be obtained directly from the author. If you use these
programs for anything interesting, let me know. If you use these
programs in a published work please cite the appropriate source(s).
DISCLAIMER
Estimating invariants from noisy time series can be risky. Do *not*
trust the output of this algorithm blindly. Any liability or problems
caused are yours!
SOURCES
C. Diks, "Estimating invariants of noisy attractors" Physical Review E
53 (1996): R4263-R4266
DJ Yu, M Small, R.G. Harrison and C. Diks, "Efficient implemntation of
the Gaussian kernel algorithm in estimating invariants and noise level
from noisy time series data" Physical Review E 61 (2000): 3750-3756
CONTACT
For further information or problems, please contact the author:
Michael Small
Electronic and Information Engineering
Hong Kong Polytechnic University
Hung Hom, Kowloon, Hong Kong
email: ensmall@polyu.edu.hk
25/2/2002