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Signals and Systems Analysis in Biomedical Engineering

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ISBN-10: 0849315573

ISBN-13: 9780849315572

Edition: 2004

Authors: Robert B. Northrop

List price: $106.95
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Description:

The interdisciplinary field of biomedical engineering requires its followers to know not only engineering skills, but also a range of material in the biological sciences. This text helps biomedical engineers strengthen their skills in the common network of applied maths that ties together these disciplines.
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Book details

List price: $106.95
Copyright year: 2004
Publisher: CRC Press LLC
Publication date: 3/12/2003
Binding: Hardcover
Pages: 432
Size: 6.25" wide x 9.25" long x 1.00" tall
Weight: 1.628

Introduction to Biomedical Signals and Systems
General Characteristics of Biomedical Signals
Introduction
Signals from physiological systems
Signals from man-made instruments
Discrete signals
Some ways to describe signals
Introduction to modulation and demodulation of physiological signals
General Properties of Physiological Systems
Introduction
Analog systems
Physiological systems
Discrete systems
Summary
Review of Linear Systems Theory
Linearity, Causality and Stationarity
Analog Systems
SISO and MIMO systems
Introduction to ODEs and their solutions
Systems Described by Sets of ODEs
Introduction
Introduction to matrix algebra
Some matrix operations
Introduction to state variables
Linear System Characterization
Introduction
System impulse response
Real convolution
Transient response of systems
Steady-state sinusoidal frequency response of LTI systems
Bode plots
Nyquist plots
Discrete Signals and Systems
Introduction
Discrete convolution
Discrete systems
The z transform pair
z Transform solutions of discrete state equations
Discussion
Stability of Systems
Chapter Summary
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
Introduction
Use of partial fraction expansions to find y(t)
Application of the laplace transform to continuous state systems
Use of signal flow graphs to find y(t) for continuous state systems
Discussion
Chapter Summary
Fourier Series Analysis of Periodic Signals
Introduction
Properties of the Fourier Series
Fourier Series Examples
Chapter Summary
The Continuous Fourier Transform
Introduction
Properties of the CFT
Analog-to-Digital Conversion and the Sampling Theorem
Introduction
Impulse modulation and the poisson sum form of the sampled spectrum
The sampling theorem
The Analytical Signal and the Hilbert Transform
Introduction
The Hilbert transform and the analytical signal
Properties of the Hilbert transform
An application of the Hilbert transform
The Modulation Transfer Function in Imaging
Introduction
The MTF
The contrast transfer function
Discussion
Chapter Summary
The Discrete Fourier Transform
Introduction
The CFT, ICFT, DFT and IDFT
The CFT and ICFT
Properties of the DFT and IDFT
Applications of the DFT and IDFT
Data Window Functions
The FFT
Introduction
The fast Fourier transform
Implementation of the FFT
Discussion
Chapter Summary
Introduction to Time-Frequency Analysis of Biomedical Signals
Introduction
The Short-Term Fourier Transform
Gabor and Adaptive Gabor Transform
Wigner-Ville and Pseudo-Wigner Transforms
Cohen's General Class of JTF Distributions
Introduction to JTFA Using Wavelets
Introduction
Computation of the continuous wavelet transform
Some wavelet basis functions, [psi] (t)
Applications of JTF Analysis to Physiological Signals
Introduction
Heart sounds
JTF analysis of EEG signals
Other biomedical applications of JTF spectrograms
JTFA Software
Chapter Summary
Introduction to the Analysis of Stationary Noise and Signals Contaminated with Noise
Introduction
Noise Descriptors and Noise in Systems
Introduction
Probability density functions
Autocorrelation
Cross-Correlation
The continuous auto- and cross-power density spectrums
Propagation of noise through stationary causal LTI continuous systems
Propagation of noise through stationary causal LTI discrete systems
Characteristic functions of random variables
Price's theorem and applications
Quantization Noise
Introduction to "data scrubbing" by nonlinear discrete filtering
Discussion
Calculation of Noise Descriptors with Finite Discrete Data
Signal Averaging and Filtering for Signal-to-Noise Ratio Improvement
Introduction
Analysis of SNR improvement by averaging
Introduction to signal-to-noise ratio improvement by linear filtering
Discussion
Introduction to the Application of Statistics and Information Theory to Genomics
Introduction
Review of DNA Biology
RNAs and the basics of protein synthesis: transcription and translation
Introduction to statistics applied to genomics
Introduction to the application of information theory to genomics
Introduction to hidden Markov models in genomics
Discussion
Chapter Summary
Basic Mathematical Tools used in the Characterization of Physiological Systems
Introduction
Some General Properties of Physiological Systems
Some Properties of Nonlinear Systems
Physical Factors Determining the Dynamic Behavior of Physiological Systems
Diffusion dynamics
Biochemical systems and mass-action kinetics
Means of Characterizing Physiological Systems
Introduction
The Nyquist stability criterion
Describing functions and the stability of closed-loop nonlinear systems
The use of Gaussian noise-based techniques to characterize physiological systems
Discussion
Chapter Summary
The Mathematics of Tomographic Imaging
Introduction
Algebraic Reconstruction
The Radon Transform
The Fourier Slice Theorem
The Filtered Back-Projection Algorithm
Chapter Summary
Appendices
Cramer's Rule
Signal Flow Graphs and Mason's Rule
Bode (Frequency Response) Plots
Computational Tools for Biomedical Signal Processing and Systems Analysis
Introduction
Simnon
National Instruments' LabVIEW Signal Processing Tools
Matlab, Simulink, and Toolkits
Summary
Bibliography and References
Index
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