Classification of Fixed Point Network Dynamics From Multiple Node Timeseries Data
The repository includes:
- Benchmark dataset for supervised classification of FP network dynamics (recorded from antennal lobe - olfactory network)
- Code implementing classification and recognition using Exclusive Threshold Reduction and Optimal Exclusive Threshold Reduction
Please refer to:
Classification of Fixed Point Network Dynamics From Multiple Node Timeseries Data
D. Blaszka, E. Sanders, J. Riffell, and E. Shlizerman
for more information.
The paper has to be cited in any use or modification of the dataset or the code.
The code is written in Matlab and for Optimal Exclusive Threshold Reduction requires the CVX package for convex optimization.
https://github.com/cvxr/CVX
After install set up CVX in MATLAB as follows:
addpath /path/to/cvx
addpath /path/to/cvx/structures
addpath /path/to/lib
addpath /path/to/functions
addpath /path/to/commands
addpath /path/to/builtins
cvx_setup
cvx_solver sdpt3
ICA modes were obtained using:
Higuera A.A.F, Garcia R.A.B., and Bermudez R.V.G. Python version of infomax independent component analysis. https:// github.com/alvarouc/ica/, 2015–2016.
#Dataset
18stim_benchmark.mat
#Run
For classification space and classifier run:
runClassification For recognition run:
runClassification_recognition