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 (fMRI)Provides
advanced tools for the detection, monitoring, separation,
localising and understanding of functional, anatomical, and
physiological abnormalities of the brainPuts 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 analysisFocuses on
multimodal and multiway adaptive processing of brain signals, the
new direction of brain signal research
General
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