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IJCNN
2008
IEEE
16 years 26 days ago
Learning adaptive subject-independent P300 models for EEG-based brain-computer interfaces
Abstract— This paper proposes an approach to learn subjectindependent P300 models for EEG-based brain-computer interfaces. The P300 models are first learned using a pool of exis...
Shijian Lu, Cuntai Guan, Haihong Zhang
ICMLA
2009
15 years 4 months ago
Learning Probabilistic Structure Graphs for Classification and Detection of Object Structures
Abstract--This paper presents a novel and domainindependent approach for graph-based structure learning. The approach is based on solving the Maximum Common SubgraphIsomorphism pro...
Johannes Hartz
UML
2005
Springer
15 years 12 months ago
UML Vs. Classical Vs. Rhapsody Statecharts: Not All Models Are Created Equal
Abstract. State machines, represented by statecharts or statechart diagrams, are an important formalism for behavioural modelling. According to the research literature, the most po...
Michelle L. Crane, Jürgen Dingel
CSMR
2010
IEEE
15 years 1 months ago
Under and Over Approximation of State Models Recovered for Ajax Applications
Abstract--In contrast to conventional multi-page Web applications, an Ajax application is developed as a single-page application in which content and structure are changed at runti...
Alessandro Marchetto, Paolo Tonella, Filippo Ricca
ESANN
2007
15 years 8 months ago
Bat echolocation modelling using spike kernels with Support Vector Regression
Abstract. From the echoes of their vocalisations bats extract information about the positions of reflectors. To gain an understanding of how target position is translated into neu...
Bertrand Fontaine, Herbert Peremans, Benjamin Schr...