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AUTOMATICA
2005
155views more  AUTOMATICA 2005»
14 years 9 months ago
Identification of MIMO Hammerstein models using least squares support vector machines
This paper studies a method for the identification of Hammerstein models based on Least Squares Support Vector Machines (LS-SVMs). The technique allows for the determination of th...
Ivan Goethals, Kristiaan Pelckmans, Johan A. K. Su...
COLING
2002
14 years 9 months ago
Detecting Errors in Corpora Using Support Vector Machines
While the corpus-based research relies on human annotated corpora, it is often said that a non-negligible amount of errors remain even in frequently used corpora such as Penn Tree...
Tetsuji Nakagawa, Yuji Matsumoto
CDC
2010
IEEE
155views Control Systems» more  CDC 2010»
14 years 4 months ago
Linear parametric noise models for Least Squares Support Vector Machines
In the identification of nonlinear dynamical models it may happen that not only the system dynamics have to be modeled but also the noise has a dynamic character. We show how to ad...
Tillmann Falck, Johan A. K. Suykens, Bart De Moor
GFKL
2007
Springer
163views Data Mining» more  GFKL 2007»
15 years 1 months ago
Fast Support Vector Machine Classification of Very Large Datasets
In many classification applications, Support Vector Machines (SVMs) have proven to be highly performing and easy to handle classifiers with very good generalization abilities. Howe...
Janis Fehr, Karina Zapien Arreola, Hans Burkhardt
ICPR
2006
IEEE
15 years 11 months ago
Mixture of Support Vector Machines for HMM based Speech Recognition
Speech recognition is usually based on Hidden Markov Models (HMMs), which represent the temporal dynamics of speech very efficiently, and Gaussian mixture models, which do non-opt...
Sven E. Krüger, Martin Schafföner, Marce...