Deep Sparse Non-Negative Neural Network for Raman Spectroscopy trained using a parts based approach with a Sparse Non-Negative Auto Encoder
The datasets are located in data\. Unzip them before running any scripts.
A version of the autoencoder have been created in jupyter. See MNIST_run.ipynb and raman_run.ipynb
The primary development have been done in spyder. See the scripts raman_run.py and MNIST_run.py for Spyder based (the use of cells) scripts.