Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	August 2014
Genre:	Naturwissensch., Medizin, Technik
	Applications of Graph Theory and Complex Networks / Applications of Nonlinear Dynamics and Chaos Theory / Applied mathematics / B / bioinformatics / Biomathematics / Complex analysis, complex variables / Digital and Analog Signal Processing / Dynamics & statics / Graph Theory / Image processing / Imaging systems & technology / Life sciences# general issues / Mathematical and Computational Biology / Mathematical physics / Neurobiology / Neurosciences / Nonlinear Optics / Physics / Physics and Astronomy / Physiological, Cellular and Medical Topics / Signal Processing / Signal, Image and Speech Processing / Speech processing systems / Statistical physics / Systems Biology / Zoology mehr...
ISBN:	9783662438497
EAN-Code:	9783662438497
Verlag:	Springer EN
Einband:	Gebunden
Sprache:	English
Serie:	Springer Series in Synergetics
Dimensionen:	H 235 mm / B 155 mm / D
Gewicht:	6269 gr
Seiten:	318
Illustration:	XVI, 318 p. 138 illus., 20 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

This book examines theoretical and applied aspects of wavelet analysis in neurophysics, describing in detail different practical applications of the wavelet theory in the areas of neurodynamics and neurophysiology and providing a review of fundamental work that has been carried out in these fields over the last decade.Chapters 1 and 2 introduce and review the relevant foundations of neurophysics and wavelet theory, respectively, pointing on one hand to the various current challenges in neuroscience and introducing on the other the mathematical techniques of the wavelet transform in its two variants (discrete and continuous) as a powerful and versatile tool for investigating the relevant neuronal dynamics.Chapter 3 then analyzes results from examining individual neuron dynamics and intracellular processes. The principles for recognizing neuronal spikes from extracellular recordings and the advantages of using wavelets to address these issues are described and combined with approaches based on wavelet neural networks (chapter 4). The features of time-frequency organization of EEG signals are then extensively discussed, from theory to practical applications (chapters 5 and 6). Lastly, the technical details of automatic diagnostics and processing of EEG signals using wavelets are examined (chapter 7).The book will be a useful resource for neurophysiologists and physicists familiar with nonlinear dynamical systems and data processing, as well as for graduate students specializing in the corresponding areas.