Abstract :
The following topics were covered: complex-value adaptive signal processing; group independent component analysis for fMRI data and ICA for joint inference of imaging, genetic, and ERP data; cognitive components of digital media; signal detection, pattern recognition and classification; blind source separation; learning in Markov models; applications; learning theory and modelling; machine learning in remote sensing data processing; speech and audio processing; scene variability and perception constancy in the visual system; Bayesian learning; brain-computer interfaces; kernel machines; and biomedical applications.
Keywords :
learning (artificial intelligence); signal processing; Bayesian learning; ICA; Markov models; audio processing; blind source separation; brain-computer interfaces; cognitive components; complex-value adaptive signal processing; digital media; fMRI data; group independent component analysis; kernel machines; learning theory; machine learning; modelling; pattern classification; pattern recognition; remote sensing data processing; signal detection; speech processing; visual system;
Conference_Titel :
Machine Learning for Signal Processing, 2009. MLSP 2009. IEEE International Workshop on
Conference_Location :
Grenoble
Print_ISBN :
978-1-4244-4947-7
DOI :
10.1109/MLSP.2009.5306249
