Signal Processing for Neuroscientists Book

Signal Processing for Neuroscientists


  • Author : Wim van Drongelen
  • Publisher : Elsevier
  • Release Date : 2006-12-18
  • Genre: Science
  • Pages : 320
  • ISBN 10 : 008046775X
  • Total Read : 93
  • File Size : 9,5 Mb

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Signal Processing for Neuroscientists Summary:

Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the ‘golden trio’ in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB®. Multiple color illustrations are integrated in the text Includes an introduction to biomedical signals, noise characteristics, and recording techniques Basics and background for more advanced topics can be found in extensive notes and appendices A Companion Website hosts the MATLAB scripts and several data files: http://www.elsevierdirect.com/companion.jsp?ISBN=9780123708670

Signal Processing for Neuroscientists Book

Signal Processing for Neuroscientists


  • Author : Wim van Drongelen
  • Publisher : Unknown
  • Release Date : 2007
  • Genre: Medical
  • Pages : 308
  • ISBN 10 : 0123708672
  • Total Read : 99
  • File Size : 6,6 Mb

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Signal Processing for Neuroscientists Summary:

Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the 'golden trio' in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB®. * Multiple color illustrations are integrated in the text * Includes an introduction to biomedical signals, noise characteristics, and recording techniques * Basics and background for more advanced topics can be found in extensive notes and appendices * A Companion Website hosts the MATLAB scripts and several data files: http://www.elsevierdirect.com/companion.jsp?ISBN=9780123708670

Signal Processing in Neuroscience Book

Signal Processing in Neuroscience


  • Author : Xiaoli Li
  • Publisher : Springer
  • Release Date : 2016-08-31
  • Genre: Medical
  • Pages : 288
  • ISBN 10 : 9789811018220
  • Total Read : 75
  • File Size : 8,8 Mb

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Signal Processing in Neuroscience Summary:

This book reviews cutting-edge developments in neural signalling processing (NSP), systematically introducing readers to various models and methods in the context of NSP. Neuronal Signal Processing is a comparatively new field in computer sciences and neuroscience, and is rapidly establishing itself as an important tool, one that offers an ideal opportunity to forge stronger links between experimentalists and computer scientists. This new signal-processing tool can be used in conjunction with existing computational tools to analyse neural activity, which is monitored through different sensors such as spike trains, local filed potentials and EEG. The analysis of neural activity can yield vital insights into the function of the brain. This book highlights the contribution of signal processing in the area of computational neuroscience by providing a forum for researchers in this field to share their experiences to date.

Statistical Signal Processing for Neuroscience and Neurotechnology Book
Score: 5
From 1 Ratings

Statistical Signal Processing for Neuroscience and Neurotechnology


  • Author : Karim G. Oweiss
  • Publisher : Academic Press
  • Release Date : 2010-09-22
  • Genre: Science
  • Pages : 433
  • ISBN 10 : 0080962963
  • Total Read : 63
  • File Size : 17,8 Mb

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Statistical Signal Processing for Neuroscience and Neurotechnology 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

Advances in Neural Signal Processing Book

Advances in Neural Signal Processing


  • Author : Ramana Vinjamuri
  • Publisher : BoD – Books on Demand
  • Release Date : 2020-09-09
  • Genre: Medical
  • Pages : 142
  • ISBN 10 : 9781789841138
  • Total Read : 85
  • File Size : 10,8 Mb

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Advances in Neural Signal Processing Summary:

Neural signal processing is a specialized area of signal processing aimed at extracting information or decoding intent from neural signals recorded from the central or peripheral nervous system. This has significant applications in the areas of neuroscience and neural engineering. These applications are famously known in the area of brain–machine interfaces. This book presents recent advances in this flourishing field of neural signal processing with demonstrative applications.

EEG Signal Processing and Feature Extraction Book
Score: 5
From 1 Ratings

EEG Signal Processing and Feature Extraction


  • Author : Li Hu
  • Publisher : Springer Nature
  • Release Date : 2019-10-12
  • Genre: Medical
  • Pages : 437
  • ISBN 10 : 9789811391132
  • Total Read : 70
  • File Size : 16,7 Mb

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EEG Signal Processing and Feature Extraction Summary:

This book presents the conceptual and mathematical basis and the implementation of both electroencephalogram (EEG) and EEG signal processing in a comprehensive, simple, and easy-to-understand manner. EEG records the electrical activity generated by the firing of neurons within human brain at the scalp. They are widely used in clinical neuroscience, psychology, and neural engineering, and a series of EEG signal-processing techniques have been developed. Intended for cognitive neuroscientists, psychologists and other interested readers, the book discusses a range of current mainstream EEG signal-processing and feature-extraction techniques in depth, and includes chapters on the principles and implementation strategies.

MATLAB for Neuroscientists Book

MATLAB for Neuroscientists


  • Author : Pascal Wallisch
  • Publisher : Academic Press
  • Release Date : 2014-01-09
  • Genre: Computers
  • Pages : 570
  • ISBN 10 : 9780123838377
  • Total Read : 91
  • File Size : 19,8 Mb

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MATLAB for Neuroscientists Summary:

MATLAB for Neuroscientists serves as the only complete study manual and teaching resource for MATLAB, the globally accepted standard for scientific computing, in the neurosciences and psychology. This unique introduction can be used to learn the entire empirical and experimental process (including stimulus generation, experimental control, data collection, data analysis, modeling, and more), and the 2nd Edition continues to ensure that a wide variety of computational problems can be addressed in a single programming environment. This updated edition features additional material on the creation of visual stimuli, advanced psychophysics, analysis of LFP data, choice probabilities, synchrony, and advanced spectral analysis. Users at a variety of levels—advanced undergraduates, beginning graduate students, and researchers looking to modernize their skills—will learn to design and implement their own analytical tools, and gain the fluency required to meet the computational needs of neuroscience practitioners. The first complete volume on MATLAB focusing on neuroscience and psychology applications Problem-based approach with many examples from neuroscience and cognitive psychology using real data Illustrated in full color throughout Careful tutorial approach, by authors who are award-winning educators with strong teaching experience

Cooperative and Graph Signal Processing Book

Cooperative and Graph Signal Processing


  • Author : Petar Djuric
  • Publisher : Academic Press
  • Release Date : 2018-07-04
  • Genre: Computers
  • Pages : 866
  • ISBN 10 : 9780128136782
  • Total Read : 94
  • File Size : 12,9 Mb

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Cooperative and Graph Signal Processing Summary:

Cooperative and Graph Signal Processing: Principles and Applications presents the fundamentals of signal processing over networks and the latest advances in graph signal processing. A range of key concepts are clearly explained, including learning, adaptation, optimization, control, inference and machine learning. Building on the principles of these areas, the book then shows how they are relevant to understanding distributed communication, networking and sensing and social networks. Finally, the book shows how the principles are applied to a range of applications, such as Big data, Media and video, Smart grids, Internet of Things, Wireless health and Neuroscience. With this book readers will learn the basics of adaptation and learning in networks, the essentials of detection, estimation and filtering, Bayesian inference in networks, optimization and control, machine learning, signal processing on graphs, signal processing for distributed communication, social networks from the perspective of flow of information, and how to apply signal processing methods in distributed settings. Presents the first book on cooperative signal processing and graph signal processing Provides a range of applications and application areas that are thoroughly covered Includes an editor in chief and associate editor from the IEEE Transactions on Signal Processing and Information Processing over Networks who have recruited top contributors for the book