bleidens / stochastic_resonance

Stochastic Resonance in Neurochaos Learning

WHEN NOISE MEETS CHAOS: STOCHASTIC RESONANCE IN NEUROCHAOS LEARNING

In this work we showcase the constrictive use of noise inherently in Neurochaos Learning for classification

Stochastic Resonance and Neurochaos Learning.

The crux of the paper is provided in the following diagram.

Video explanation on YouTube on the usage of chaotic maps as feature extraction and highlighting chief ideas and inspiration.

Reference Paper:

1. Balakrishnan, Harikrishnan Nellippallil, et al. "ChaosNet: A chaos based artificial neural network architecture for classification." Chaos: An Interdisciplinary Journal of Nonlinear Science 29.11 (2019): 113125.

2. Harikrishnan, N. B., and Nithin Nagaraj. "Neurochaos Inspired Hybrid Machine Learning Architecture for Classification." 2020 International Conference on Signal Processing and Communications (SPCOM). IEEE, 2020.

Dependencies

• Python 3
• Numpy
• Numba

License

Copyright 2020 Harikrishnan N. B., and Nithin Nagaraj

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

   http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.