In this book, the field of adaptive learning and processing is extended to arguably one of its most important contexts which is the understanding and analysis of brain signals. No attempt is made to comment on physiological aspects of brain activity; instead, signal processing methods are developed and used to assist clinical findings. Recent developments in detection, estimation and separation of diagnostic cues from different modality neuroimaging systems are discussed.
These include constrained nonlinear signal processing techniques which incorporate sparsity, nonstationarity, multimodal data, and multiway techniques.
Key features:
* Covers advanced and adaptive signal processing techniques for the processing of electroencephalography (EEG) and magneto-encephalography (MEG) signals, and their correlation to the corresponding functional magnetic resonance imaging (f MRI)
* Provides advanced tools for the detection, monitoring, separation, localising and understanding of functional, anatomical, and physiological abnormalities of the brain
* Puts a major emphasis on brain dynamics and how this can be evaluated for the assessment of brain activity in various states such as for brain-computer interfacing emotions and mental fatigue analysis
* Focuses on multimodal and multiway adaptive processing of brain signals, the new direction of brain signal research
Despre autor
Dr Saeid Sanei, Reader in Biomedical Signal Processing and
Deputy Head of Computing Department, Faculty of Engineering and
Physical Sciences, University of Surrey, Guildford,
Surrey, United Kingdom.
Dr Sanei received his Ph D from Imperial College of Science,
Technology and Medicine, London, in Biomedical Signal and Image
Processing in 1991. He has made a major contribution to
Electroencephalogram (EEG) analysis; blind source separation,
sparse component analysis and compressive sensing; parallel factor
analysis and tensor factorization; particle filtering; chaos and
time series analysis; support vector machines; hidden Markov
models; and brain computer interfacing (BCI).He has published over
180 papers in refereed journals and conference proceedings, and a
book on EEG Signal Processing. He has served as an editor, member
of the technical committee, and reviewer for a number of journals
and conferences, and has recently been selected as the Biomedical
Signal Processing Track Chair for the IEEE Engineering in Medicine
and Biology Conference 2009. His international collaborations
involve both educational and industrial organizations, including
the RIKEN Brain Science Research Institute in Japan. He also
teaches extensively at both undergraduate and postgraduate
level.
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