Complex-Valued Neural Networks (CVNN)

Done by @NEGU93 - J. Agustin Barrachina

This is a library that uses Tensorflow as a back-end to do complex-valued neural networks as, as far as I know, CVNNs are barely supported by Tensorflow and not even supported yet for pytorch (reason why I decided to use Tensorflow for this library).

Documentation

Please Read the Docs

Instalation Guide:

Using Anaconda

conda install -c negu93 cvnn

Using PIP

Vanilla Version installs all the minimum dependencies.

pip install cvnn

Plot capabilities has the posibility to plot the results obtained with the training with several plot libraries.

pip install cvnn[plotter]

Full Version installs full version with all features

pip install cvnn[full]

Short example

import numpy as np
from cvnn.layers import ComplexDense
from cvnn.cvnn_model import CvnnModel
from tensorflow.keras.losses import categorical_crossentropy

# Assume you already have complex data 'x' with its labels 'y'...
x, y = get_dataset()        # to be done by each user

shape = [ComplexDense(output_size=100, input_size=np.shape(x)[1], activation='cart_relu'),
        ComplexDense(output_size=40, activation='cart_relu'),
        ComplexDense(output_size=np.shape(y)[1], activation='softmax_real')]
model = CvnnModel("cvnn_example", shape, categorical_crossentropy)
model.fit(x, y, batch_size=100, epochs=150)

About me & Motivation

My personal website

I am a PhD student from Ecole CentraleSupelec with a scholarship from ONERA and the DGA

I am basically working with Complex-Valued Neural Networks for my PhD topic. In the need of making my coding more dynamic I build a library not to have to repeat the same code over and over for little changes and accelerate therefore my coding.

Cite Me

Code:

@MISC {NEGU93-CVNN,
    author       = {J. Agustin Barrachina},
    title        = {Complex-Valued Neural Networks (CVNN)},
    howpublished = {\url{https://github.com/NEGU93/cvnn}},
    doi          = {10.5281/zenodo.4140245},
    journal      = {GitHub repository},
    year         = {2019}
}

I recommend changing the year and adding a version item with the one you used.

Or cite the Zenodo version:

@software{j_agustin_barrachina_2020_4140245,
  author       = {J Agustin Barrachina},
  title        = {NEGU93/cvnn: First official release},
  month        = oct,
  year         = 2020,
  publisher    = {Zenodo},
  version      = {v0.3.40},
  doi          = {10.5281/zenodo.4140245},
  url          = {https://doi.org/10.5281/zenodo.4140245}
}

Paper:

@misc{barrachina2020complexvalued,
    title={Complex-Valued vs. Real-Valued Neural Networks for Classification Perspectives: An Example on Non-Circular Data},
    author={Jose Agustin Barrachina and Chenfang Ren and Christele Morisseau and Gilles Vieillard and Jean-Philippe Ovarlez},
    year={2020},
    eprint={2009.08340},
    archivePrefix={arXiv},
    primaryClass={stat.ML}
}