Practical Biomedical Signal Analysis Using Matlab
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Practical Biomedical Signal Analysis Using Matlab
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Author : Katarzyn J. Blinowska
language : en
Publisher: CRC Press
Release Date : 2011-09-12
Practical Biomedical Signal Analysis Using Matlab written by Katarzyn J. Blinowska and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-12 with Medical categories.
Practical Biomedical Signal Analysis Using MATLAB® presents a coherent treatment of various signal processing methods and applications. The book not only covers the current techniques of biomedical signal processing, but it also offers guidance on which methods are appropriate for a given task and different types of data. The first several chapters of the text describe signal analysis techniques—including the newest and most advanced methods—in an easy and accessible way. MATLAB routines are listed when available and freely available software is discussed where appropriate. The final chapter explores the application of the methods to a broad range of biomedical signals, highlighting problems encountered in practice. A unified overview of the field, this book explains how to properly use signal processing techniques for biomedical applications and avoid misinterpretations and pitfalls. It helps readers to choose the appropriate method as well as design their own methods.
Practical Guide For Biomedical Signals Analysis Using Machine Learning Techniques
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Author : Abdulhamit Subasi
language : en
Publisher: Academic Press
Release Date : 2019-03-16
Practical Guide For Biomedical Signals Analysis Using Machine Learning Techniques written by Abdulhamit Subasi and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-16 with Medical categories.
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
Practical Biomedical Signal Analysis Using Matlab
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Author : Katarzyna J. Blinowska-Cieslak
language : en
Publisher:
Release Date : 2012
Practical Biomedical Signal Analysis Using Matlab written by Katarzyna J. Blinowska-Cieslak and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Electrophysiology categories.
Practical Biomedical Signal Analysis Using Matlab
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Author : Katarzyna J. Blinowska
language : en
Publisher: CRC Press
Release Date : 2021-10-26
Practical Biomedical Signal Analysis Using Matlab written by Katarzyna J. Blinowska and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-26 with Medical categories.
Covering the latest cutting-edge techniques in biomedical signal processing while presenting a coherent treatment of various signal processing methods and applications, this second edition of Practical Biomedical Signal Analysis Using MATLAB® also offers practical guidance on which procedures are appropriate for a given task and different types of data. It begins by describing signal analysis techniques—including the newest and most advanced methods in the field—in an easy and accessible way, illustrating them with Live Script demos. MATLAB® routines are listed when available, and freely available software is discussed where appropriate. The book concludes by exploring the applications of the methods to a broad range of biomedical signals while highlighting common problems encountered in practice. These chapters have been updated throughout and include new sections on multiple channel analysis and connectivity measures, phase-amplitude analysis, functional near-infrared spectroscopy, fMRI (BOLD) signals, wearable devices, multimodal signal analysis, and brain-computer interfaces. By providing a unified overview of the field, this book explains how to integrate signal processing techniques in biomedical applications properly and explores how to avoid misinterpretations and pitfalls. It helps readers to choose the appropriate method as well as design their own methods. It will be an excellent guide for graduate students studying biomedical engineering and practicing researchers in the field of biomedical signal analysis. Features: Fully updated throughout with new achievements, technologies, and methods and is supported with over 40 original MATLAB Live Scripts illustrating the discussed techniques, suitable for self-learning or as a supplement to college courses Provides a practical comparison of the advantages and disadvantages of different approaches in the context of various applications Applies the methods to a variety of signals, including electric, magnetic, acoustic, and optical Katarzyna J. Blinowska is a Professor emeritus at the University of Warsaw, Poland, where she was director of Graduate Studies in Biomedical Physics and head of the Department of Biomedical Physics. Currently, she is employed at the Institute of Biocybernetics and Biomedical Engineering of the Polish Academy of Sciences. She has been at the forefront in developing new advanced time-series methods for research and clinical applications. Jarosław Żygierewicz is a Professor at the University of Warsaw, Poland. His research focuses on developing methods for analyzing EEG and MEG signals, brain-computer interfaces, and applications of machine learning in signal processing and classification.
Biomedical Signal And Image Processing
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Author : Kayvan Najarian
language : en
Publisher: CRC Press
Release Date : 2016-04-19
Biomedical Signal And Image Processing written by Kayvan Najarian and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Computers categories.
Written for senior-level and first year graduate students in biomedical signal and image processing, this book describes fundamental signal and image processing techniques that are used to process biomedical information. The book also discusses application of these techniques in the processing of some of the main biomedical signals and images, such as EEG, ECG, MRI, and CT. New features of this edition include the technical updating of each chapter along with the addition of many more examples, the majority of which are MATLAB based.
Biomedical Signal Analysis
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Author : Rangaraj M. Rangayyan
language : en
Publisher: John Wiley & Sons
Release Date : 2015-04-24
Biomedical Signal Analysis written by Rangaraj M. Rangayyan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-24 with Science categories.
The book will help assist a reader in the development of techniques for analysis of biomedical signals and computer aided diagnoses with a pedagogical examination of basic and advanced topics accompanied by over 350 figures and illustrations. Wide range of filtering techniques presented to address various applications 800 mathematical expressions and equations Practical questions, problems and laboratory exercises Includes fractals and chaos theory with biomedical applications
Digital Signal Processing Using Matlab For Students And Researchers
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Author : John W. Leis
language : en
Publisher: John Wiley & Sons
Release Date : 2011-10-14
Digital Signal Processing Using Matlab For Students And Researchers written by John W. Leis and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-10-14 with Science categories.
Quickly Engages in Applying Algorithmic Techniques to Solve Practical Signal Processing Problems With its active, hands-on learning approach, this text enables readers to master the underlying principles of digital signal processing and its many applications in industries such as digital television, mobile and broadband communications, and medical/scientific devices. Carefully developed MATLAB® examples throughout the text illustrate the mathematical concepts and use of digital signal processing algorithms. Readers will develop a deeper understanding of how to apply the algorithms by manipulating the codes in the examples to see their effect. Moreover, plenty of exercises help to put knowledge into practice solving real-world signal processing challenges. Following an introductory chapter, the text explores: Sampled signals and digital processing Random signals Representing signals and systems Temporal and spatial signal processing Frequency analysis of signals Discrete-time filters and recursive filters Each chapter begins with chapter objectives and an introduction. A summary at the end of each chapter ensures that one has mastered all the key concepts and techniques before progressing in the text. Lastly, appendices listing selected web resources, research papers, and related textbooks enable the investigation of individual topics in greater depth. Upon completion of this text, readers will understand how to apply key algorithmic techniques to address practical signal processing problems as well as develop their own signal processing algorithms. Moreover, the text provides a solid foundation for evaluating and applying new digital processing signal techniques as they are developed.
Practical Biomedical Signal Analysis Using Matlab
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Author : Katarzyn Blinowska
language : en
Publisher: CRC Press
Release Date : 2011-09-12
Practical Biomedical Signal Analysis Using Matlab written by Katarzyn Blinowska and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-12 with Medical categories.
Practical Biomedical Signal Analysis Using MATLAB presents a coherent treatment of various signal processing methods and applications. The book not only covers the current techniques of biomedical signal processing, but it also offers guidance on which methods are appropriate for a given task and different types of data.The first several chapters o
Introduction To Applied Statistical Signal Analysis
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Author : Richard Shiavi
language : en
Publisher: Elsevier
Release Date : 2010-07-19
Introduction To Applied Statistical Signal Analysis written by Richard Shiavi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-19 with Technology & Engineering categories.
Introduction to Applied Statistical Signal Analysis, Third Edition, is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech. Topics presented include mathematical bases, requirements for estimation, and detailed quantitative examples for implementing techniques for classical signal analysis. This book includes over one hundred worked problems and real world applications. Many of the examples and exercises use measured signals, most of which are from the biomedical domain. The presentation style is designed for the upper level undergraduate or graduate student who needs a theoretical introduction to the basic principles of statistical modeling and the knowledge to implement them practically. Includes over one hundred worked problems and real world applications. Many of the examples and exercises in the book use measured signals, many from the biomedical domain.