• If you make use of this DDVFA code please cite the following paper

[1] L. E. Brito da Silva, I. Elnabarawy, and D. C. Wunsch II, "Distributed dual vigilance fuzzy adaptive resonance theory learns online, retrieves arbitrarily-shaped clusters, and mitigates order dependence," Neural Networks. To appear.

and refer to this Applied Computational Intelligence Laboratory (ACIL) Github repository as

[2] L. E. Brito da Silva, I. Elnabarawy, and D. C. Wunsch II, "Distributed Dual Vigilance Fuzzy ART," 2019. [Online].
Available: https://github.com/ACIL-Group/DDVFA

• The data sets used in the experiments section of the Distributed Dual Vigilance Fuzzy ART paper are available at:

1. UCI machine learning repository:
   http://archive.ics.uci.edu/ml

2. Fundamental Clustering Problems Suite (FCPS):
   https://www.uni-marburg.de/fb12/arbeitsgruppen/datenbionik/data?language_sync=1

3. Datasets package:
   https://www.researchgate.net/publication/239525861_Datasets_package

4. Clustering basic benchmark:
   http://cs.uef.fi/sipu/datasets

• The "main_example.m" file contains an example of usage of the code provided.