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» Extraction of Logical Rules from Neural Networks
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ICASSP
2011
IEEE
12 years 11 months ago
Belief theoretic methods for soft and hard data fusion
In many contexts, one is confronted with the problem of extracting information from large amounts of different types soft data (e.g., text) and hard data (from e.g., physics-based...
Thanuka Wickramarathne, Kamal Premaratne, Manohar ...
IJCNN
2008
IEEE
14 years 2 months ago
Filter Bank Common Spatial Pattern (FBCSP) in Brain-Computer Interface
—In motor imagery-based Brain Computer Interfaces (BCI), discriminative patterns can be extracted from the electroencephalogram (EEG) using the Common Spatial Pattern (CSP) algor...
Kai Keng Ang, Zhang Yang Chin, Haihong Zhang, Cunt...
DATAMINE
2006
224views more  DATAMINE 2006»
13 years 8 months ago
Characteristic-Based Clustering for Time Series Data
With the growing importance of time series clustering research, particularly for similarity searches amongst long time series such as those arising in medicine or finance, it is cr...
Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman
INFOCOM
2009
IEEE
14 years 2 months ago
Minimizing Rulesets for TCAM Implementation
—Packet classification is a function increasingly used in a number of networking appliances and applications. Typically, sists of a set of abstract classifications, and a set o...
Rick McGeer, Praveen Yalagandula
TJS
2010
182views more  TJS 2010»
13 years 6 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari