Signal Processing for Neuroscientists (Relié)

Signal Processing for Neuroscientists, Second Edition provides an introduction for those with a modest understanding of algebra, trigonometry, and calculus. Combining the previous edition (2006), its more advanced companion volume (2010), anda set of new related topics, it features eight new or extended chapters and a new set of exercises developed by the author over the past decade. The combination of signal processing and a new, strong modeling component results in a significant didactic resource for the neuroscientist, beginning with the fundamentals and moving to practical applications of numerical recipes and simulations of neural activity.
This book presents a fundamental and uncluttered background for students of neuroscience, the nonspecialist scientist, or engineer. It is a starting point to develop applications and allows the reader to interpret and master the field of signal processing and modeling. Key Features : Includes an introduction to biomedical signals, noise characteristics, recording techniques, fundamentals of linear and nonlinear systems analysis, and multichannel analysis that were previously split into two separate volumes ; Features new chapters on modeling fundamentals, applications to modeling neuronal and network activity, and novel introductions to the Kalman filter, medical imaging, and multitaper power spectrum estimation ; Includes practical examples of algorithm development and implementation in MATLAB® and a new set of exercises with each chapter ; Features a companion website that hosts the MATLAB® scripts, data files, answers to selected exercises, figures, and (links to) video lectures.