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Signals and Systems in Biomedical Engineering: Signal Processing and Physiological Systems Modeling (Topics in Biomedical Engineering International Book Series)

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Signals and Systems in Biomedical Engineering: Signal Processing and Physiological Systems Modeling (Topics in Biomedical Engineering International Book Series) Cover

 

Synopses & Reviews

Publisher Comments:

This book fills a critical gap in biomedical data analysis in making the connection between signal processing and physiological modeling. Based on the premise that the use of signal processing techniques is predicated on explicit or implicit models, this book provides a foundation in systems analysis and signal processing techniques for physiological data. The book comprises two main parts: namely, signal processing techniques for linear systems, and physiological modeling. Beginning with a broad introduction to signals and systems, the book proceeds to contemporary techniques in digital signal processing. While maintaining continuity of mathematical concepts, the emphasis is on practical implementation and applications. The signal processing topics covered include Fourier transform, the wavelet transform, and optimal filtering techniques. The book presumes only knowledge of college mathematics and is suitable for a beginner in the subject; however, a student with a previous course in analog and digital signal processing will find that only a third of the book contains a bare treatment of classical signal processing. The extensive use of diagrams illustrates the graphical nature of modern signal processing, and provides easy descriptions of practical techniques and their shortcomings. Each chapter has a number of illustrative examples and exercises. The accompanying software provides exercises in convolution, sampling, Fourier analysis and wavelet decomposition that illustrate the use of these techniques as well as their shortcomings. The latter part of the book discusses techniques of physiological modeling, contrasting biophysical models with black-box models, and experimental procedures used in such modeling. Model-based data analysis including noise reduction and feature extraction in physiology are discussed in detail. Several numerical simulation exercises are also outlined for the student.

Synopsis:

This book fills a critical gap in biomedical data analysis in making the connection between signal processing and physiological modeling. Based on the premise that the use of signal processing techniques is predicated on explicit or implicit models, this book provides a foundation in systems analysis and signal processing techniques for physiological data. The book comprises two main parts: namely, signal processing techniques for linear systems, and physiological modeling. Beginning with a broad introduction to signals and systems, the book proceeds to contemporary techniques in digital signal processing. While maintaining continuity of mathematical concepts, the emphasis is on practical implementation and applications. The signal processing topics covered include Fourier transform, the wavelet transform, and optimal filtering techniques. The book presumes only knowledge of college mathematics and is suitable for a beginner in the subject; however, a student with a previous course in analog and digital signal processing will find that only a third of the book contains a bare treatment of classical signal processing. The extensive use of diagrams illustrates the graphical nature of modern signal processing, and provides easy descriptions of practical techniques and their shortcomings. Each chapter has a number of illustrative examples and exercises. The accompanying software provides exercises in convolution, sampling, Fourier analysis and wavelet decomposition that illustrate the use of these techniques as well as their shortcomings. The latter part of the book discusses techniques of physiological modeling, contrasting biophysical models with black-box models, and experimentalprocedures used in such modeling. Model-based data analysis including noise reduction and feature extraction in physiology are discussed in detail. Several numerical simulation exercises are also outlined for the student.

Synopsis:

"Signals and Systems in Biomedical Engineering" a book/CDmultimedia package, begins with a broad introduction to signals andsystems and then proceeds to contemporary techniques in digital signalprocessing. In the latter part of "Signals and Systems in BiomedicalEngineering," Devasahayam delves into his area of expertise anddiscusses techniques of physiological modeling, contrastingbiophysical models with black-box models, and the experimentalprocedures in such modeling. Model based data analysis including noisereduction and feature extraction in physiology are discussed indetail."Signals and Systems in Biomedical Engineering" maintains acontinuity of mathematical concepts, while emphasizing practicalimplementations and applications. Each chapter is filled withillustrative examples and exercises on such topics as the Fouriertransform, the wavelet transform and optimal filtering techniques.Several numerical simulation exercises are also outlined for thestudent. The accompanying software provides additional exercises inconvolution, sampling, Fourier analysis and wavelet decomposition.This book/CD package is well suited for today's multimedia classroom."Signals and Systems in Biomedical Engineering" is designed as atextbook, or for use as supplementary reading for senior undergraduateand graduate students in a biomedical engineering program. "Signalsand" "Systems in Biomedical Engineering" presumes only basicknowledge of college mathematics and is suitable for a beginner in thesubject; however, a student with a previous course in analog anddigital signal will find that less than a third of the book contains abare treatment of classical signal processing.

Description:

System requirements for accompanying computer disc: PC and Windows95 or later operating system. Includes bibliographical references and index.

Table of Contents

Acknowledgments. Preface. 1. Introduction to Systems Analysis and Numerical Methods. 2. Continuous Time Signals and Systems. 3. Fourier Analysis for Continuous Time Processes. 4. Discrete Time Signals and Systems. 5. Fourier Analysis for Discrete-Time Processes. 6. Time-Frequency and Wavelet Analysis. 7. Estimation of Signals in Noise. 8. Feedback Systems. 9. Model Based Analysis of Physiological Signals. 10. Modeling the Nerve Action Potential. 11. Modeling Skeletal Muscle Contraction. 12. Modeling Myoelectric Activity. 13. System Identification in Physiology. 14. Modeling the Cardiovascular System. 15. A Model of the Immune Response to Disease. Appendix. Bibliography. Index.

Product Details

ISBN:
9780306463914
Editor:
Devasahayam, Suresh R.
Publisher:
Springer
Editor:
Devasahayam, Suresh R.
Author:
Devasahayam, Suresh R.
Location:
New York
Subject:
Physiology
Subject:
Biotechnology
Subject:
Signal processing
Subject:
Biomedical Engineering
Subject:
Scanning systems
Subject:
Models, Biological.
Subject:
Models, Theoretical.
Subject:
Signal Processing, Computer-Assisted.
Subject:
Imaging Systems
Subject:
Signal, Image and Speech Processing
Subject:
Biophysics and Biological Physics
Subject:
Electrical engineering
Subject:
Health and Medicine-Medical Specialties
Subject:
Engineering - General
Copyright:
Edition Description:
Book with CD-ROM
Series:
Topics in biomedical engineering international book series
Publication Date:
20000630
Binding:
HARDCOVER
Language:
English
Illustrations:
Yes
Pages:
354
Dimensions:
26 cm. +

Related Subjects

Health and Self-Help » Health and Medicine » Medical Specialties
Humanities » Philosophy » General
Reference » Science Reference » Technology

Signals and Systems in Biomedical Engineering: Signal Processing and Physiological Systems Modeling (Topics in Biomedical Engineering International Book Series) New Hardcover
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Product details 354 pages Kluwer Academic/Plenum Publishers - English 9780306463914 Reviews:
"Synopsis" by , This book fills a critical gap in biomedical data analysis in making the connection between signal processing and physiological modeling. Based on the premise that the use of signal processing techniques is predicated on explicit or implicit models, this book provides a foundation in systems analysis and signal processing techniques for physiological data. The book comprises two main parts: namely, signal processing techniques for linear systems, and physiological modeling. Beginning with a broad introduction to signals and systems, the book proceeds to contemporary techniques in digital signal processing. While maintaining continuity of mathematical concepts, the emphasis is on practical implementation and applications. The signal processing topics covered include Fourier transform, the wavelet transform, and optimal filtering techniques. The book presumes only knowledge of college mathematics and is suitable for a beginner in the subject; however, a student with a previous course in analog and digital signal processing will find that only a third of the book contains a bare treatment of classical signal processing. The extensive use of diagrams illustrates the graphical nature of modern signal processing, and provides easy descriptions of practical techniques and their shortcomings. Each chapter has a number of illustrative examples and exercises. The accompanying software provides exercises in convolution, sampling, Fourier analysis and wavelet decomposition that illustrate the use of these techniques as well as their shortcomings. The latter part of the book discusses techniques of physiological modeling, contrasting biophysical models with black-box models, and experimentalprocedures used in such modeling. Model-based data analysis including noise reduction and feature extraction in physiology are discussed in detail. Several numerical simulation exercises are also outlined for the student.
"Synopsis" by , "Signals and Systems in Biomedical Engineering" a book/CDmultimedia package, begins with a broad introduction to signals andsystems and then proceeds to contemporary techniques in digital signalprocessing. In the latter part of "Signals and Systems in BiomedicalEngineering," Devasahayam delves into his area of expertise anddiscusses techniques of physiological modeling, contrastingbiophysical models with black-box models, and the experimentalprocedures in such modeling. Model based data analysis including noisereduction and feature extraction in physiology are discussed indetail."Signals and Systems in Biomedical Engineering" maintains acontinuity of mathematical concepts, while emphasizing practicalimplementations and applications. Each chapter is filled withillustrative examples and exercises on such topics as the Fouriertransform, the wavelet transform and optimal filtering techniques.Several numerical simulation exercises are also outlined for thestudent. The accompanying software provides additional exercises inconvolution, sampling, Fourier analysis and wavelet decomposition.This book/CD package is well suited for today's multimedia classroom."Signals and Systems in Biomedical Engineering" is designed as atextbook, or for use as supplementary reading for senior undergraduateand graduate students in a biomedical engineering program. "Signalsand" "Systems in Biomedical Engineering" presumes only basicknowledge of college mathematics and is suitable for a beginner in thesubject; however, a student with a previous course in analog anddigital signal will find that less than a third of the book contains abare treatment of classical signal processing.
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