Signal processing for neuroscientists : introduction to the analysis of physiological signals /

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Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the golden trio i...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Drongelen, Wim van
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam ; Boston : Elsevier/Academic Press, ©2007.
Temas:
Signal processing > Digital techniques.
Neurosciences > Data processing.
Neurology > Mathematical models.
Physiology > Mathematical models.
Life sciences.
Physical sciences.
Mathematical models.
Neurosciences.
Computing Methodologies
Investigative Techniques
Biological Science Disciplines
Natural Science Disciplines
Analytical, Diagnostic and Therapeutic Techniques and Equipment
Information Science
Disciplines and Occupations
Models, Theoretical
Signal Processing, Computer-Assisted
Neurosciences
Traitement du signal > Techniques numériques.
Neurologie > Modèles mathématiques.
Physiologie > Modèles mathématiques.
Sciences de la vie.
Sciences physiques.
Modèles mathématiques.
biological sciences.
physical sciences.
mathematical models.
COMPUTERS > Information Theory.
TECHNOLOGY & ENGINEERING > Signals & Signal Processing.
Physical sciences
Mathematical models
Life sciences
Neurology > Mathematical models
Neurosciences > Data processing
Physiology > Mathematical models
Signal processing > Digital techniques
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Introduction
  • Data Acquisition
  • Noise
  • Signal Averaging
  • Real and Complex Fourier Series
  • Continuous, Discrete, and Fast Fourier Transform
  • Fourier Transform Applications
  • LTI systems, Convolution, Correlation, and Coherence
  • Laplace and z-Transform
  • Introduction to Filters: the RC-Circuit
  • Filters: Analysis
  • Filters: Specification, Bode plot, Nyquist plot
  • Filters: Digital Filters
  • Spike Train Analysis
  • Wavelet Analysis: Time Domain Properties
  • Wavelet Analysis: Frequency Domain Properties
  • Nonlinear Techniques.

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