Statistical Signal Processing for Neuroscience and Neurotechnology

This book PDF is perfect for those who love Science genre, written by Karim G. Oweiss and published by Academic Press which was released on 22 September 2010 with total hardcover pages 433. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Statistical Signal Processing for Neuroscience and Neurotechnology books below.

Statistical Signal Processing for Neuroscience and Neurotechnology
Author : Karim G. Oweiss
File Size : 54,8 Mb
Publisher : Academic Press
Language : English
Release Date : 22 September 2010
ISBN : 0080962963
Pages : 433 pages
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Statistical Signal Processing for Neuroscience and Neurotechnology by Karim G. Oweiss Book PDF Summary

This is a uniquely comprehensive reference that summarizes the state of the art of signal processing theory and techniques for solving emerging problems in neuroscience, and which clearly presents new theory, algorithms, software and hardware tools that are specifically tailored to the nature of the neurobiological environment. It gives a broad overview of the basic principles, theories and methods in statistical signal processing for basic and applied neuroscience problems. Written by experts in the field, the book is an ideal reference for researchers working in the field of neural engineering, neural interface, computational neuroscience, neuroinformatics, neuropsychology and neural physiology. By giving a broad overview of the basic principles, theories and methods, it is also an ideal introduction to statistical signal processing in neuroscience. A comprehensive overview of the specific problems in neuroscience that require application of existing and development of new theory, techniques, and technology by the signal processing community Contains state-of-the-art signal processing, information theory, and machine learning algorithms and techniques for neuroscience research Presents quantitative and information-driven science that has been, or can be, applied to basic and translational neuroscience problems

Statistical Signal Processing for Neuroscience and Neurotechnology

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