Semiblind Source Separation of Climate Data Detects El Ni no as the Component with the Highest Interannual Variability

Reference:

Alexander Ilin, Harri Valpola, and Erkki Oja. Semiblind source separation of climate data detects El Ni no as the component with the highest interannual variability. In Proceedings of the IEEE International Joint Conference on Neural Networks (IJCNN 2005), pages 1722–1727, Montréal, Québec, Canada, August 2005.

Suggested BibTeX entry:

@inproceedings{Ilin05_elnino,
    address = {Montr\'{e}al, Qu\'{e}bec, Canada},
    author = {Alexander Ilin and Harri Valpola and Erkki Oja},
    booktitle = {Proceedings of the IEEE International Joint Conference on Neural Networks ({IJCNN} 2005)},
    month = {August},
    pages = {1722--1727},
    title = {Semiblind Source Separation of Climate Data Detects {E}l {N}i\~{n}o as the Component with the Highest Interannual Variability},
    year = {2005},
}