Independent component analysis by general nonlinear Hebbian-like learning rules
Signal Processing - Special issue on neural networks
Natural gradient works efficiently in learning
Neural Computation
Complexity Pursuit: Separating Interesting Components from Time Series
Neural Computation
Equivariant adaptive source separation
IEEE Transactions on Signal Processing
A Bit Level Representation for Time Series Data Mining with Shape Based Similarity
Data Mining and Knowledge Discovery
2006 Special issue: Exploratory analysis of climate data using source separation methods
Neural Networks - 2006 special issue: Earth sciences and environmental applications of computational intelligence
Mining usage web log via independent component analysis and rough fuzzy
AIKED'06 Proceedings of the 5th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases
CAREY: ClimAtological contRol of EmergencY regions
OTM'11 Proceedings of the 2011th Confederated international conference on On the move to meaningful internet systems
International Journal of Data Analysis Techniques and Strategies
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In this article, we apply the independent component analysis technique for mining spatio-temporal data. The technique has been applied to mine for patterns in weather data using the North Atlantic Oscillation (NAO) as a specific example. We find that the strongest independent components match the observed synoptic weather patterns corresponding to the NAO. We also validate our results by matching the independent component activities with the NAO index.