llvqi / post-nonlinear_mixture_learning

This is a code demo for post-nonlinear mixture learning under simplex structure.

Post-Nonlinear Mixture Learning under Simplex Structure

This is a code demo for the following paper:

Qi Lyu and Xiao Fu, 'Identifiability-Guaranteed Simplex-Structured Post-Nonlinear Mixture Learning via Autoencoder', IEEE Transactions on Signal Processing, vol. 69, pp. 4921-4936, 2021.

If you find this repo helpful, please consider citing our paper.

@ARTICLE{lyu2021identifiability,
author={Lyu, Qi and Fu, Xiao},
journal={IEEE Transactions on Signal Processing},
title={Identifiability-Guaranteed Simplex-Structured Post-Nonlinear Mixture Learning via Autoencoder},
year={2021},
volume={69},
pages={4921-4936}}

Run command 'bash run_simplex_demo.sh' to generate the results of Fig. 4 in the paper.

Tested on: python 3.5, PyTorch 1.1.0, cuda 9.0.