Nonlinear Modeling Advanced Black-Box Techniques
Description
Nonlinear Modeling: Advanced Black-Box Techniques discusses methods on
It also contains the results of the K.U. Leuven time series prediction competition, held within the framework of an international workshop at the K.U. Leuven, Belgium in July 1998.
- Neural nets and related model structures for nonlinear system identification;
- Enhanced multi-stream Kalman filter training for recurrent networks;
- The support vector method of function estimation;
- Parametric density estimation for the classification of acoustic feature vectors in speech recognition;
- Wavelet-based modeling of nonlinear systems;
- Nonlinear identification based on fuzzy models;
- Statistical learning in control and matrix theory;
- Nonlinear time-series analysis.
It also contains the results of the K.U. Leuven time series prediction competition, held within the framework of an international workshop at the K.U. Leuven, Belgium in July 1998.
Keywords
Language Arts & DisciplinesLibrary & Information ScienceMathematicsSciencePhysicsMathematical & ComputationalSystem TheoryTechnology & EngineeringElectricalElectronicsCircuitsEngineering (General)Imaging SystemsIndustrial DesignSignals & Signal Processing
1998Book
Author(s)Johan A. K. Suykens
PublisherSpringer Science & Business Media
ISBN9780792381952
LanguageEnglish
