CoCoNAD-m - CoCoNAD for MatLab/Octave
Download
The lastest version can always be found on the
web page of Kristian Loewe, who maintains these sources.
Description
CoCoNAD-m makes the CoCoNAD implementation
in C available as functions in MatLab/Octave. Details can be found on
the
web page of Kristian Loewe, who is the maintainer of the
MatLab/Octave bindings.
References
More information about the CoCoNAD algorithm can be found
in the following papers:
- Frequent
Item Set Mining for Sequential Data:
Synchrony in Neuronal Spike Trains
David Picado-Muiño and Christian Borgelt
Intelligent Data Analysis 18(6):997-1012.
IOS Press, Amsterdam, Netherlands 2014
doi:10.3233/IDA-140681
iospress.com
(16 pages)
- Finding
Frequent Patterns in Parallel Point Processes
Christian Borgelt and David Picado-Muiño
Proc. 12th Int. Symposium on Intelligent Data Analysis,
116-126.
Springer-Verlag, Berlin/Heidelberg, Germany 2013
ida_13.pdf (443 kb)
ida_13.ps.gz (491 kb)
(11 pages)
A description of the methods of pattern spectrum filtering and
pattern set reduction can be found in the following papers:
- Finding
Neural Assemblies with Frequent Item Set Mining
David Picado-Muiño, Christian Borgelt, Denise Berger,
George Gerstein, and Sonja Grün
Frontiers in Neuroinformatics 7:article 9
Frontiers Media, Lausanne, Switzerland 2013
doi:10.3389/fninf.2013.00009
frontiersin.org
accfim.pdf (1797 kb)
accfim.ps.gz (772 kb)
(14 pages)
- Statistical Evaluation
of Synchronous Spike Patterns Extracted by Frequent Itemset
Mining
Emiliano Torre, David Picado-Muiño, Michael Denker,
Christian Borgelt, and Sonja Grün
Frontiers in Computational Neuroscience,
7:article 132
Frontiers Media, Lausanne, Switzerland 2013
doi:10.3389/fncom.2013.00132
frontiersin.org
(13 pages)
Pattern spectrum estimation is described in the following paper:
- Simple Pattern Spectrum Estimation
for Fast Pattern Filtering with CoCoNAD
Christian Borgelt and David Picado-Muiño
Proc. 13th Int. Symposium on Intelligent Data Analysis,
37-48.
Springer-Verlag, Berlin/Heidelberg, Germany 2014
ida_14.pdf (1224 kb)
ida_14.ps.gz (1190 kb)
(11 pages)