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Titlebook: Advanced Biosignal Processing; Amine Naït-Ali Book 2009 Springer-Verlag Berlin Heidelberg 2009 Elektroenzephalografie.Radiologieinformatio

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Flossing als Sonderform der Kompression,resentations (e.g., wavelet networks) allow to describe these oscillations with a small set of parameters automatically. Using appropriate training algorithms, wavelet networks can also be applied for ERP single-trial analysis (low SNR) to investigate trial-to-trial variabilities.
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Behandlungstechniken in der Narbentherapier the surrounding EEG fulfils any necessary condition concerning the properties of signal and noise known from the detection theory. Further, there is a strong nonlinear and time-variant relation between the stimulation sequence and the evoked response. Thus, for a reliable detection, optimization o
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https://doi.org/10.1007/978-3-031-01509-0irst step aims to detect all events in this signal and to identify these events by allocating them to physiological classes: contractions, foetus motions, Alvarez or Long Duration Low Frequency (LDBF) waves. The second step consists of the identification of contractions between normal contractions a
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Jaqueline Vago Ferrari,Elizeu Borloti multiclassifier approaches are described for this purpose. Single classifiers include: certainty-based classifiers, classifiers based on the nearest neighbour decision rule: the fuzzy k-NN classifiers, and classifiers that use a correlation measure as an estimation of the degree of similarity betwe
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Basic Concepts of Behavioral Pharmacologyd/or the shape of some biosignals. The class of optimization techniques that will be covered encompasses Genetic and Particle Swarm Optimization family of optimization methods. Both methods belong to a specific optimization category called “metaheuristics”. Two specific examples will illustrate the
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Basic Concepts of Behavioral Pharmacologyerefore, biological processes are all non-stationary and highly nonlinear. Thus the study of biomedical processes, which are heavily depending on observations, is crucially dependent on the data analysis. The newly developed method, the Hilbert-Huang Transform (HHT), is ideally suited for nonlinear
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