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» Neural methods for non-standard data
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ISNN
2011
Springer
14 years 7 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
ESANN
2003
15 years 5 months ago
Locally Linear Embedding versus Isotop
Abstract. Recently, a new method intended to realize conformal mappings has been published. Called Locally Linear Embedding (LLE), this method can map high-dimensional data lying o...
John Aldo Lee, Cédric Archambeau, Michel Ve...
SP
2008
IEEE
159views Security Privacy» more  SP 2008»
15 years 3 months ago
Inferring neuronal network connectivity from spike data: A temporal data mining approach
Abstract. Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent developments in electrophysiology an...
Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishn...
IJCNN
2006
IEEE
15 years 10 months ago
Nominal-scale Evolving Connectionist Systems
— A method is presented for extending the Evolving Connectionist System (ECoS) algorithm that allows it to explicitly represent and learn nominal-scale data without the need for ...
Michael J. Watts
HIS
2003
15 years 5 months ago
Decision Support Systems Using Hybrid Neurocomputing
This paper suggests a decision support system for tactical air combat environment where not much prior information is available about the decision regions. We proposed a combinati...
Cong Tran, Ajith Abraham, Lakhmi C. Jain