RosenPy

What is RosenPy?

• A complex-valued neural network library, written in Python;
• Incorporates CVNNs such as CV-FFNN (complex-valued feedforward neural network), SC-FFNN (split-complex feedforward neural network), CV-RBFNN (complex-valued radial basis function neural network), FC-RBFNN (fully-complex radial basis function neural network), and Deep PT-RBFNN (deep phase transmittance radial basis function neural network);
• It enables the incorporation of properties intrinsic to neural networks, such as momentum, L2 regularization, early stopping, mini-batch, and learning rate decay.
• New version available at: https://github.com/ariadneac/rosenpy-v2.1

Dependencies

• Python3.6+, Numpy

Authors

• Ariadne Arrais Cruz – ariadne.arrais@gmail.com
• Kayol Soares Mayer – kayolmayer@gmail.com
• Dalton Soares Arantes – dalton@unicamp.br

License

RosenPy is an open source framework distributed under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

RosenPy is distributed in the hope that it will be useful to every user, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public Licens for more details.

Please contact the authors or Inova/Unicamp (software@inova.unicamp.br) for commercial use permissions, premium support or customized solutions based on RosenPy.

We kindly ask that reference to RosenPy should be done as:

@ARTICLE{Ariadne2022, author = {Ariadne Arrais Cruz, Kayol Soares Mayer, Dalton Soares Arantes}, title = {{RosenPy: an Open Source Python Framework for Complex-Valued Neural Networks}}, journal = {Software X}, year = {2022}, volume = {??}, number = {??}, pages = {?-??}, doi={??} }