dendritic-neuron-BSS

Code to run the experiment 1 of the paper:

Modeling Repetition-based BSS with Dendritic Neurons

Giorgia Dellaferrera, Toshitake Asabuki, Tomoki Fukai

https://www.frontiersin.org/articles/10.3389/fnins.2022.855753/full

Frontiers in Neuroscience (2022)

Requirements

We run the experiments with the following:

Numpy framework: Python 3.6.5, Numpy 1.17.3

Libraries:

librosa 0.7.1, scipy 1.1.0, sklearn 0.19.1, matplotlib 2.2.2, pylab, pydub,

Experiments

The main experiments are run through Recovering_sound_sources_matlab_mult.py.

For example, to run with the standard settings:

python Recovering_sound_sources_matlab_mult.py --exp_name Experiment1 \
    --n_sounds 2 --N 8 

Substitute --n_sounds 2 with --n_sounds 3 to run the experiment with a larger number of mixtures.

Substitute --N 8 with N 12 to run the experiment with a larger number of output neurons.

Add --all_comb to run the experiment in the "all combination" set up.

Add --sparse_connectivity to modify the network from fully connected to sparse connectivity.

Citation tools

Please cite our work as:

@ARTICLE{10.3389/fnins.2022.855753, AUTHOR={Dellaferrera, Giorgia and Asabuki, Toshitake and Fukai, Tomoki},
TITLE={Modeling the Repetition-Based Recovering of Acoustic and Visual Sources With Dendritic Neurons},
JOURNAL={Frontiers in Neuroscience},
VOLUME={16},
YEAR={2022},
URL={https://www.frontiersin.org/article/10.3389/fnins.2022.855753},
DOI={10.3389/fnins.2022.855753},
ISSN={1662-453X},
}