Signals and Systems Analysis In Biomedical Engineering  book cover
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2nd Edition

Signals and Systems Analysis In Biomedical Engineering




ISBN 9781439812518
Published March 26, 2010 by CRC Press
654 Pages - 215 B/W Illustrations

 
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Book Description

The first edition of this text, based on the author’s 30 years of teaching and research on neurosensory systems, helped biomedical engineering students and professionals strengthen their skills in the common network of applied mathematics that ties together the diverse disciplines that comprise this field. Updated and revised to include new material as the field has grown, Signals and Systems Analysis in Biomedical Engineering, Second Edition continues to provide a ready source of information on those specialized mathematical techniques most useful in describing and analyzing biomedical signals.

New chapters on nonlinear and complex systems

Enriched with many examples that promote sound practical analysis, this volume covers classical linear systems theory and its applications to biomedicine. It examines the important use of joint time-frequency analysis to characterize non-stationary physiological signals, and explores the mathematics of tomographic imaging (the Radon transform, the Fourier slice theorem, and the filtered back-projection algorithm). It also describes the analytical signal and the Hilbert transform and some of its biomedical applications. New chapters in this edition include one on the analysis of nonlinear biochemical systems and biochemical oscillators, as well as one introducing complex systems and illustrating ways to best model them.

Four appendices with additional material

Extensive appendices supplement the text, including "Simnon® Programs Used in Chapters 11 and 12," "How to use Root Locus to Determine the Stability of SISO Linear Systems," "Signal Flow Graphs and Mason’s Rule," and "Computational Tools for Biomedical Signal Processing and Systems Analysis." An extensive glossary is included as well as an ample listing of sources for further study.

A solutions manual is available for instructors wishing to convert this refrence to classroom use.

Table of Contents

Introduction to Biomedical Signals and Systems
General Characteristics of Biomedical Signals
General Properties of PSs
Review of Linear Systems Theory
Linearity, Causality, and Stationarity
Analog Systems
Systems Described by Sets of ODEs
Linear System Characterization
Discrete Signals and Systems
Stability of Systems
The Laplace Transform and Its Applications
Introduction
Properties of the Laplace Transform
Some Examples of Finding Laplace Transforms
The Inverse Laplace Transform
Applications of the Laplace Transform
Fourier Series Analysis of Periodic Signals
Introduction
Properties of the FS
FS Examples
The Continuous Fourier Transform
Introduction
Properties of the CFT
ADC and the Sampling Theorem
The Analytical Signal and the HT
MTF in Imaging
The Discrete Fourier Transform
Introduction
The CFT, ICFT, DFT, and IDFT
Data Window Functions
The FFT
Introduction to Joint TimeFrequency Analysis of Biomedical Signals
Introduction
The Short-Term Fourier Transform
The Gabor and Adaptive Gabor Transforms
The WignerVille and PseudoWigner Transforms
Cohen’s General Class of JTF Distributions
Introduction to JTFA Using Wavelets
Applications of JTFA to Physiological Signals
JTFA Software
Introduction to the Analysis of Stationary Noise, and Signals Contaminated with Noise
Introduction
Noise Descriptors and Noise in Systems
Calculation of Noise Descriptors with Finite Discrete Data
Signal Averaging and Filtering for SNR Improvement
Introduction to the Application of Statistics and IT to Genomics
Basic Mathematical Tools Used in the Characterization of Physiological Systems
Introduction
Some General Properties of PSs
Some Properties of Nonlinear Systems
Physical Factors Determining the Dynamic Behavior of PSs
Means of Characterizing PSs
Introduction to the Mathematics of Tomographic Imaging
Introduction
Algebraic Reconstruction
The Radon Transform
The Fourier Slice Theorem
Filtered BackProjection Algorithm
Introduction to the Analysis of Nonlinear Biochemical Systems and Biochemical Oscillators
Introduction: Some General Properties of Nonlinear Systems
All Living Systems Are Nonlinear
Parametric Regulation in Nonlinear Biological Systems
Approaches to Nonlinear Analysis: the Phase Plane
Chaos, Stability, and Limit Cycles in Nonlinear Biological Systems
Introduction to Complex Systems in Biology and Medicine
Introduction to Complex Systems
When Is a System Complex?
Some Examples
Properties of Complex Systems: Chaos and Tipping Points
The Law of Unintended Consequences
Why Study Complex Systems?
Human Responses to Complexity
Complex Systems Engineering
Some Complex Physiological Regulatory Systems
Structure and Function: Some Examples of Complex Physiological Regulatory Systems and Their Simplified Models
Examples of When Complex Physiological Systems Fail
Some Approaches to Dealing with Complexity in an Organized Manner
Glossary
Appendix A
Appendix B
Appendix C
Appendix D
Index

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Author(s)

Biography

Robert B. Northrop graduated with a bachelor’s degree in electrical engineering from the Massachusetts Institute of Technology in 1956. At the University of Connecticut (UCONN), he received a master’s degree in systems engineering in 1958. As the result of a long-standing interest in physiology, he entered a PhD program at UCONN in physiology, doing research on the neuromuscular physiology of molluskan catch muscles. He received his PhD in 1964. His current research interest lies in complex systems. Dr. Northrop was on the electrical and computer engineering faculty at UCONN until his retirement in June 1997. Throughout this time, he was director of the BME graduate program. As emeritus professor, he still teaches courses in BME, writes texts, sails, and travels. He lives in Chaplin, CT, with his wife, and a smooth fox terrier.