Code for implementing the paper EFFECT OF INJECTED NOISE IN DEEP NEURAL NETWORKS

Requirements

python 2.7, numpy, scikit-learn, scipy

Running the code

src folder contains the python scripts. The MNIST database can be found in the data folder.

Run the file run_hid_4_network2.py to implement a deep network with 4 hidden layers and 50 neurons in each WITHOUT noise. python run_hid_4_network2.py

Run the file run_hid_4_network2_aoi.py to implement a deep network with 4 hidden layers and 50 neurons in each with AOI noise. python run_hid_4_network2_aoi.py

Run the file run_hid_4_network2_aoi_randn.py to implement a deep network with 4 hidden layers and 50 neurons in each with AOI noise with randomness. python run_hid_4_network2_aoi_randn.py

Run the file run_hid_4_network2_line_noise.py to implement a deep network with 4 hidden layers and 50 neurons in each with line noise. python run_hid_4_network2_line_noise.py

License

MIT License

Copyright (c) 2017 Naresh Nagabushan

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.