Signal Processing for Neuroscientists

Signal Processing for Neuroscientists
Author: Wim van Drongelen
Publsiher: Elsevier
Total Pages: 320
Release: 2006-12-18
ISBN 10: 9780080467757
ISBN 13: 008046775X
Language: EN, FR, DE, ES & NL

Signal Processing for Neuroscientists Book Review:

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

Signal Processing for Neuroscientists
Author: Wim van Drongelen
Publsiher: Unknown
Total Pages: 308
Release: 2007
ISBN 10: 9780123708670
ISBN 13: 0123708672
Language: EN, FR, DE, ES & NL

Signal Processing for Neuroscientists Book Review:

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

Signal Processing for Neuroscientists
Author: Wim van Drongelen
Publsiher: Academic Press
Total Pages: 740
Release: 2018-04-20
ISBN 10: 012810483X
ISBN 13: 9780128104835
Language: EN, FR, DE, ES & NL

Signal Processing for Neuroscientists Book Review:

Signal Processing for Neuroscientists, Second Edition provides an introduction to signal processing and modeling for those with a modest understanding of algebra, trigonometry and calculus. With a robust modeling component, this book describes modeling from the fundamental level of differential equations all the way up to practical applications in neuronal modeling. It features nine new chapters and an exercise section developed by the author. Since the modeling of systems and signal analysis are closely related, integrated presentation of these topics using identical or similar mathematics presents a didactic advantage and a significant resource for neuroscientists with quantitative interest. Although each of the topics introduced could fill several volumes, this book provides a fundamental and uncluttered background for the non-specialist scientist or engineer to not only get applications started, but also evaluate more advanced literature on signal processing and modeling. Includes an introduction to biomedical signals, noise characteristics, recording techniques, and the more advanced topics of linear, nonlinear and multi-channel systems analysis Features new chapters on the fundamentals of modeling, application to neuronal modeling, Kalman filter, multi-taper power spectrum estimation, and practice exercises Contains the basics and background for more advanced topics in extensive notes and appendices Includes practical examples of algorithm development and implementation in MATLAB Features a companion website with MATLAB scripts, data files, figures and video lectures

Statistical Signal Processing for Neuroscience and Neurotechnology

Statistical Signal Processing for Neuroscience and Neurotechnology
Author: Karim G. Oweiss
Publsiher: Academic Press
Total Pages: 433
Release: 2010-09-22
ISBN 10: 9780080962962
ISBN 13: 0080962963
Language: EN, FR, DE, ES & NL

Statistical Signal Processing for Neuroscience and Neurotechnology Book Review:

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

Web Application Obfuscation

Web Application Obfuscation
Author: Mario Heiderich,Eduardo Alberto Vela Nava,Gareth Heyes,David Lindsay
Publsiher: Elsevier
Total Pages: 296
Release: 2011-01-13
ISBN 10: 1597496057
ISBN 13: 9781597496056
Language: EN, FR, DE, ES & NL

Web Application Obfuscation Book Review:

Web applications are used every day by millions of users, which is why they are one of the most popular vectors for attackers. Obfuscation of code has allowed hackers to take one attack and create hundreds-if not millions-of variants that can evade your security measures. Web Application Obfuscation takes a look at common Web infrastructure and security controls from an attacker's perspective, allowing the reader to understand the shortcomings of their security systems. Find out how an attacker would bypass different types of security controls, how these very security controls introduce new types of vulnerabilities, and how to avoid common pitfalls in order to strengthen your defenses. Named a 2011 Best Hacking and Pen Testing Book by InfoSec Reviews Looks at security tools like IDS/IPS that are often the only defense in protecting sensitive data and assets Evaluates Web application vulnerabilties from the attacker's perspective and explains how these very systems introduce new types of vulnerabilities Teaches how to secure your data, including info on browser quirks, new attacks and syntax tricks to add to your defenses against XSS, SQL injection, and more

Signal Processing for Neuroscientists A Companion Volume

Signal Processing for Neuroscientists  A Companion Volume
Author: Wim van Drongelen
Publsiher: Elsevier
Total Pages: 186
Release: 2010-08-26
ISBN 10: 0123849160
ISBN 13: 9780123849168
Language: EN, FR, DE, ES & NL

Signal Processing for Neuroscientists A Companion Volume Book Review:

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 toward some of the more complex analysis techniques. This book is a companion to the previously published 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 multi-channel recordings. Covers the more advanced topics of linear and nonlinear systems analysis and multi-channel analysis Includes practical examples implemented in MATLAB Provides multiple references to the basics to help the student

Signal Processing in Auditory Neuroscience

Signal Processing in Auditory Neuroscience
Author: Yoichi Ando
Publsiher: Academic Press
Total Pages: 120
Release: 2018-05-22
ISBN 10: 0128159391
ISBN 13: 9780128159392
Language: EN, FR, DE, ES & NL

Signal Processing in Auditory Neuroscience Book Review:

Signal Processing in Auditory Neuroscience: Temporal and Spatial Features of Sound and Speech discusses how the physical attributes of different sounds manifest in neural signals and how to tease-apart their different influences. It includes EEG/MEG as additional variables to be considered when studying neural mechanisms of auditory processing in general, specifically in speech. Focuses on signal processing in human auditory-neuroscience Contains information that will be useful to researchers using a MEG/EEG recording of brain activity to study neural mechanisms of auditory processing and speech Gives an important overview and methodological background for techniques that are useful in human auditory-neuroscience

EEG Signal Processing and Feature Extraction

EEG Signal Processing and Feature Extraction
Author: Li Hu,Zhiguo Zhang
Publsiher: Springer Nature
Total Pages: 437
Release: 2019-10-12
ISBN 10: 9811391130
ISBN 13: 9789811391132
Language: EN, FR, DE, ES & NL

EEG Signal Processing and Feature Extraction Book Review:

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.

Analyzing Neural Time Series Data

Analyzing Neural Time Series Data
Author: Mike X Cohen
Publsiher: MIT Press
Total Pages: 600
Release: 2014-01-17
ISBN 10: 0262019876
ISBN 13: 9780262019873
Language: EN, FR, DE, ES & NL

Analyzing Neural Time Series Data Book Review:

A comprehensive guide to the conceptual, mathematical, and implementational aspects of analyzing electrical brain signals, including data from MEG, EEG, and LFP recordings.

Signal Processing in Neuroscience

Signal Processing in Neuroscience
Author: Xiaoli Li
Publsiher: Springer
Total Pages: 288
Release: 2016-08-31
ISBN 10: 9811018227
ISBN 13: 9789811018220
Language: EN, FR, DE, ES & NL

Signal Processing in Neuroscience Book Review:

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.

MATLAB for Neuroscientists

MATLAB for Neuroscientists
Author: Pascal Wallisch,Michael E. Lusignan,Marc D. Benayoun,Tanya I. Baker,Adam Seth Dickey,Nicholas G. Hatsopoulos
Publsiher: Academic Press
Total Pages: 570
Release: 2014-01-09
ISBN 10: 0123838371
ISBN 13: 9780123838377
Language: EN, FR, DE, ES & NL

MATLAB for Neuroscientists Book Review:

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

MATLAB for Brain and Cognitive Scientists

MATLAB for Brain and Cognitive Scientists
Author: Mike X Cohen
Publsiher: MIT Press
Total Pages: 576
Release: 2017-05-12
ISBN 10: 0262035820
ISBN 13: 9780262035828
Language: EN, FR, DE, ES & NL

MATLAB for Brain and Cognitive Scientists Book Review:

An introduction to a popular programming language for neuroscience research, taking the reader from beginning to intermediate and advanced levels of MATLAB programming.

Dynamic Neuroscience

Dynamic Neuroscience
Author: Zhe Chen,Sridevi V. Sarma
Publsiher: Springer
Total Pages: 327
Release: 2017-12-27
ISBN 10: 3319719769
ISBN 13: 9783319719764
Language: EN, FR, DE, ES & NL

Dynamic Neuroscience Book Review:

This book shows how to develop efficient quantitative methods to characterize neural data and extra information that reveals underlying dynamics and neurophysiological mechanisms. Written by active experts in the field, it contains an exchange of innovative ideas among researchers at both computational and experimental ends, as well as those at the interface. Authors discuss research challenges and new directions in emerging areas with two goals in mind: to collect recent advances in statistics, signal processing, modeling, and control methods in neuroscience; and to welcome and foster innovative or cross-disciplinary ideas along this line of research and discuss important research issues in neural data analysis. Making use of both tutorial and review materials, this book is written for neural, electrical, and biomedical engineers; computational neuroscientists; statisticians; computer scientists; and clinical engineers.

Computational Neuroscience

Computational Neuroscience
Author: Hanspeter A Mallot
Publsiher: Springer Science & Business Media
Total Pages: 135
Release: 2013-05-23
ISBN 10: 3319008617
ISBN 13: 9783319008615
Language: EN, FR, DE, ES & NL

Computational Neuroscience Book Review:

Computational Neuroscience - A First Course provides an essential introduction to computational neuroscience and equips readers with a fundamental understanding of modeling the nervous system at the membrane, cellular, and network level. The book, which grew out of a lecture series held regularly for more than ten years to graduate students in neuroscience with backgrounds in biology, psychology and medicine, takes its readers on a journey through three fundamental domains of computational neuroscience: membrane biophysics, systems theory and artificial neural networks. The required mathematical concepts are kept as intuitive and simple as possible throughout the book, making it fully accessible to readers who are less familiar with mathematics. Overall, Computational Neuroscience - A First Course represents an essential reference guide for all neuroscientists who use computational methods in their daily work, as well as for any theoretical scientist approaching the field of computational neuroscience.

EEG ERP Analysis

EEG ERP Analysis
Author: Kamel Nidal,Aamir Saeed Malik
Publsiher: CRC Press
Total Pages: 334
Release: 2014-10-23
ISBN 10: 1482224712
ISBN 13: 9781482224719
Language: EN, FR, DE, ES & NL

EEG ERP Analysis Book Review:

Changes in the neurological functions of the human brain are often a precursor to numerous degenerative diseases. Advanced EEG systems and other monitoring systems used in preventive diagnostic procedures incorporate innovative features for brain monitoring functions such as real-time automated signal processing techniques and sophisticated amplifiers. Highlighting the US, Europe, Australia, New Zealand, Japan, Korea, China, and many other areas, EEG/ERP Analysis: Methods and Applications examines how researchers from various disciplines have started to work in the field of brain science, and explains the different techniques used for processing EEG/ERP data. Engineers can learn more about the clinical applications, while clinicians and biomedical scientists can familiarize themselves with the technical aspects and theoretical approaches. This book explores the recent advances involved in EEG/ERP analysis for brain monitoring, details successful EEG and ERP applications, and presents the neurological aspects in a simplified way so that those with an engineering background can better design clinical instruments. It consists of 13 chapters and includes the advanced techniques used for signal enhancement, source localization, data fusion, classification, and quantitative EEG. In addition, some of the chapters are contributed by neurologists and neurosurgeons providing the clinical aspects of EEG/ERP analysis. Covers a wide range of EEG/ERP applications with state-of-the-art techniques for denoising, analysis, and classification Examines new applications related to 3D display devices Includes MATLAB® codes EEG/ERP Analysis: Methods and Applications is a resource for biomedical and neuroscience scientists who are working on neural signal processing and interpretation, and biomedical engineers who are working on EEG/ERP signal analysis methods and developing clinical instrumentation. It can also assist neurosurgeons, psychiatrists, and postgraduate students doing research in neural engineering, as well as electronic engineers in neural signal processing and instrumentation.

Methods in Insect Sensory Neuroscience

Methods in Insect Sensory Neuroscience
Author: Thomas A. Christensen
Publsiher: CRC Press
Total Pages: 464
Release: 2004-12-20
ISBN 10: 1420039423
ISBN 13: 9781420039429
Language: EN, FR, DE, ES & NL

Methods in Insect Sensory Neuroscience Book Review:

Insects are among the most diverse and adaptable organisms on Earth. They have long been our chief competitors for food and are responsible for spreading devastating afflictions such as malaria and encephalitis. The insects’ ability to thrive is due in large part to their well-developed sensory systems, which present a host of novel physiological, biochemical, and behavioral attributes that underlie their remarkable feats of sensory performance. Methods in Insect Neuroscience is the first text to showcase the tremendous variety of methods that are available to study the sensory capabilities of insects. It covers the complete spectrum of sensory modalities in insects, from vision and audition, to chemoreception and multimodal processing. The book is designed to serve as a how to guide for putting into practice a wide range of techniques, including behavioral observation, brain imaging, single- and multi-unit electrophysiology, computer modeling/signal processing, and robotics to address innumerable questions. A truly multidisciplinary synthesis of neurobiological, behavioral, and computational approaches to sensory-information processing is most likely to yield our richest understanding of the mechanisms that underlie sensation and perception. In that spirit, this book contains chapters by leading neuroethologists, comparative biologists, neuroscientists, computational biologists, geneticists, and bioengineers who have adopted insects as their models. Their hard work and dedication is evident in the quality of detail contained in every chapter. This book is intended for seasoned neuroscientists looking for state-of-the-art information, as well as discussions on the open-ended questions facing sensory neuroscience today. It is also intended as a primer for newcomers utilizing insects to embark on a study of sensory mechanisms.The opening section provides background information and references about the basic organization of the insect brain and the behavioral strategies used by insects to navigate their complex and varied environments. The latter sections are designed to provide more detailed information about specific sensory modalities and the tools that are used to study them.

Brain Computer Interfacing

Brain Computer Interfacing
Author: Rajesh P. N. Rao
Publsiher: Cambridge University Press
Total Pages: 337
Release: 2013-09-30
ISBN 10: 0521769418
ISBN 13: 9780521769419
Language: EN, FR, DE, ES & NL

Brain Computer Interfacing Book Review:

The idea of interfacing minds with machines has long captured the human imagination. Recent advances in neuroscience and engineering are making this a reality, opening the door to restoration and augmentation of human physical and mental capabilities. Medical applications such as cochlear implants for the deaf and neurally controlled prosthetic limbs for the paralyzed are becoming almost commonplace. Brain-computer interfaces (BCIs) are also increasingly being used in security, lie detection, alertness monitoring, telepresence, gaming, education, art, and human augmentation. This introduction to the field is designed as a textbook for upper-level undergraduate and first-year graduate courses in neural engineering or brain-computer interfacing for students from a wide range of disciplines. It can also be used for self-study and as a reference by neuroscientists, computer scientists, engineers, and medical practitioners. Key features include questions and exercises in each chapter and a supporting website.

Correlative Learning

Correlative Learning
Author: Zhe Chen,Simon Haykin,Jos J. Eggermont,Suzanna Becker
Publsiher: John Wiley & Sons
Total Pages: 480
Release: 2008-01-07
ISBN 10: 0470171448
ISBN 13: 9780470171448
Language: EN, FR, DE, ES & NL

Correlative Learning Book Review:

Correlative Learning: A Basis for Brain and Adaptive Systems provides a bridge between three disciplines: computational neuroscience, neural networks, and signal processing. First, the authors lay down the preliminary neuroscience background for engineers. The book also presents an overview of the role of correlation in the human brain as well as in the adaptive signal processing world; unifies many well-established synaptic adaptations (learning) rules within the correlation-based learning framework, focusing on a particular correlative learning paradigm, ALOPEX; and presents case studies that illustrate how to use different computational tools and ALOPEX to help readers understand certain brain functions or fit specific engineering applications.

Complexity and Nonlinearity in Cardiovascular Signals

Complexity and Nonlinearity in Cardiovascular Signals
Author: Riccardo Barbieri,Enzo Pasquale Scilingo,Gaetano Valenza
Publsiher: Springer
Total Pages: 537
Release: 2017-08-09
ISBN 10: 3319587099
ISBN 13: 9783319587097
Language: EN, FR, DE, ES & NL

Complexity and Nonlinearity in Cardiovascular Signals Book Review:

This book reports on the latest advances in complex and nonlinear cardiovascular physiology aimed at obtaining reliable, effective markers for the assessment of heartbeat, respiratory, and blood pressure dynamics. The chapters describe in detail methods that have been previously defined in theoretical physics such as entropy, multifractal spectra, and Lyapunov exponents, contextualized within physiological dynamics of cardiovascular control, including autonomic nervous system activity. Additionally, the book discusses several application scenarios of these methods. The text critically reviews the current state-of-the-art research in the field that has led to the description of dedicated experimental protocols and ad-hoc models of complex physiology. This text is ideal for biomedical engineers, physiologists, and neuroscientists. This book also: Expertly reviews cutting-edge research, such as recent advances in measuring complexity, nonlinearity, and information-theoretic concepts applied to coupled dynamical systems Comprehensively describes applications of analytic technique to clinical scenarios such as heart failure, depression and mental disorders, atrial fibrillation, acute brain lesions, and more Broadens readers' understanding of cardiovascular signals, heart rate complexity, heart rate variability, and nonlinear analysis

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques
Author: Abdulhamit Subasi
Publsiher: Academic Press
Total Pages: 456
Release: 2019-03-16
ISBN 10: 0128176733
ISBN 13: 9780128176733
Language: EN, FR, DE, ES & NL

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques Book Review:

Practical Guide for Biomedical Signals Analysis Using Machine Learning Techniques: A MATLAB Based Approach presents how machine learning and biomedical signal processing methods can be used in biomedical signal analysis. Different machine learning applications in biomedical signal analysis, including those for electrocardiogram, electroencephalogram and electromyogram are described in a practical and comprehensive way, helping readers with limited knowledge. Sections cover biomedical signals and machine learning techniques, biomedical signals, such as electroencephalogram (EEG), electromyogram (EMG) and electrocardiogram (ECG), different signal-processing techniques, signal de-noising, feature extraction and dimension reduction techniques, such as PCA, ICA, KPCA, MSPCA, entropy measures, and other statistical measures, and more. This book is a valuable source for bioinformaticians, medical doctors and other members of the biomedical field who need a cogent resource on the most recent and promising machine learning techniques for biomedical signals analysis. Provides comprehensive knowledge in the application of machine learning tools in biomedical signal analysis for medical diagnostics, brain computer interface and man/machine interaction Explains how to apply machine learning techniques to EEG, ECG and EMG signals Gives basic knowledge on predictive modeling in biomedical time series and advanced knowledge in machine learning for biomedical time series