Statistical Signal Processing for Neuroscience and Neurotechnology
- Karim G. Oweiss, Associate Professor, Electrical and Computer Engineering, Michigan State University, East Lansing, MI, USA
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.
Signal processing engineers in electrical and electronic engineering; biomedical engineers; applied mathematicians and statisticians; computational neuroscientists