Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources

Cite

Text

Lee et al. "Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources." Neural Computation, 1999. doi:10.1162/089976699300016719

Markdown

[Lee et al. "Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources." Neural Computation, 1999.](https://mlanthology.org/neco/1999/lee1999neco-independent/) doi:10.1162/089976699300016719

BibTeX

@article{lee1999neco-independent,
  title     = {{Independent Component Analysis Using an Extended Infomax Algorithm for Mixed Sub-Gaussian and Super-Gaussian Sources}},
  author    = {Lee, Te-Won and Girolami, Mark A. and Sejnowski, Terrence J.},
  journal   = {Neural Computation},
  year      = {1999},
  pages     = {417-441},
  doi       = {10.1162/089976699300016719},
  volume    = {11},
  url       = {https://mlanthology.org/neco/1999/lee1999neco-independent/}
}