Signal processing for neuroscientists : a companion volume : advanced topics, nonlinear techniques and multi-channel analysis / Wim van Drongelen
Item type | Current library | Call number | Status | Date due | Barcode | |
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La bibliothèque de l'ESPCI Salle de lecture | NE-020 (Browse shelf(Opens below)) | Available | NE-020 |
Références bibliographiques
Lomb's Algorithm and the Hilbert Transform Modeling Volterra Series Wiener Series Poisson-Wiener Series Decomposition of Multi-Channel Data Causality
The popularity of signal processing in neuroscience is increasing and with the current availability and development of computer hardware and software it is anticipated that the current growth will continue. Because electrode fabrication has improved and measurement equipment is getting less expensive, electrophysiological measurements with large numbers of channels are now very common. In addition, neuroscience has entered the age of light and fluorescence measurements are fully integrated into the researcher's toolkit. Because each image in a movie contains multiple pixels, these measurements are multi-channel by nature. Furthermore, the availability of both generic and specialized software packages for data analysis has altered the neuroscientist's attitude towards some of the more complex analysis techniques. This book is a companion to the previously published book, 'Signal Processing for Neuroscientists: An Introduction to the Analysis of Physiological Signals', which introduced readers to the basic concepts. It discusses several advanced techniques, rediscovers methods to describe nonlinear systems, and examines the analysis of mulit-channel recordings
Elsevier Science & Technology 1101653:10954061