Signal Processing for Neuroscientists
eBook - ePub

Signal Processing for Neuroscientists

  1. 740 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Signal Processing for Neuroscientists

About this book

Signal Processing for Neuroscientists, Second Edition provides an introduction to signal processing and modeling for those with a modest understanding of algebra, trigonometry and calculus. With a robust modeling component, this book describes modeling from the fundamental level of differential equations all the way up to practical applications in neuronal modeling. It features nine new chapters and an exercise section developed by the author. Since the modeling of systems and signal analysis are closely related, integrated presentation of these topics using identical or similar mathematics presents a didactic advantage and a significant resource for neuroscientists with quantitative interest. Although each of the topics introduced could fill several volumes, this book provides a fundamental and uncluttered background for the non-specialist scientist or engineer to not only get applications started, but also evaluate more advanced literature on signal processing and modeling. - Includes an introduction to biomedical signals, noise characteristics, recording techniques, and the more advanced topics of linear, nonlinear and multi-channel systems analysis - Features new chapters on the fundamentals of modeling, application to neuronal modeling, Kalman filter, multi-taper power spectrum estimation, and practice exercises - Contains the basics and background for more advanced topics in extensive notes and appendices - Includes practical examples of algorithm development and implementation in MATLAB - Features a companion website with MATLAB scripts, data files, figures and video lectures

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Table of contents

  1. Cover image
  2. Title page
  3. Table of Contents
  4. Copyright
  5. Dedication
  6. Preface to the Second Edition
  7. Preface to the Companion Volume
  8. Preface to the First Edition
  9. Chapter 1. Introduction
  10. Chapter 2. Data Acquisition
  11. Chapter 3. Noise
  12. Chapter 4. Signal Averaging
  13. Chapter 5. Real and Complex Fourier Series
  14. Chapter 6. Continuous, Discrete, and Fast Fourier Transform
  15. Chapter 7. 1-D and 2-D Fourier Transform Applications
  16. Chapter 8. Lomb's Algorithm and Multitaper Power Spectrum Estimation
  17. Chapter 9. Differential Equations: Introduction
  18. Chapter 10. Differential Equations: Phase Space and Numerical Solutions
  19. Chapter 11. Modeling
  20. Chapter 12. Laplace and z-Transform
  21. Chapter 13. LTI Systems: Convolution, Correlation, Coherence, and the Hilbert Transform
  22. Chapter 14. Causality
  23. Chapter 15. Introduction to Filters: The RC-Circuit
  24. Chapter 16. Filters: Analysis
  25. Chapter 17. Filters: Specification, Bode Plot, Nyquist Plot
  26. Chapter 18. Filters: Digital Filters
  27. Chapter 19. Kalman Filter
  28. Chapter 20. Spike Train Analysis
  29. Chapter 21. Wavelet Analysis: Time Domain Properties
  30. Chapter 22. Wavelet Analysis: Frequency Domain Properties
  31. Chapter 23. Low-Dimensional Nonlinear Dynamics: Fixed Points, Limit Cycles, and Bifurcations
  32. Chapter 24. Volterra Series
  33. Chapter 25. Wiener Series
  34. Chapter 26. Poisson–Wiener Series
  35. Chapter 27. Nonlinear Techniques
  36. Chapter 28. Decomposition of Multichannel Data
  37. Chapter 29. Modeling Neural Systems: Cellular Models
  38. Chapter 30. Modeling Neural Systems: Network Models
  39. Index

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Yes, you can access Signal Processing for Neuroscientists by Wim van Drongelen in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Medical Theory, Practice & Reference. We have over one million books available in our catalogue for you to explore.