Circuits, Signals and Systems for Bioengineers

Series-Page_2018_Circuits--Signals-and-Systems-for-Bioengineers
	Series page
Front-Matter_2018_Circuits--Signals-and-Systems-for-Bioengineers
	Circuits, Signals, and Systems for Bioengineers
Copyright_2018_Circuits--Signals-and-Systems-for-Bioengineers
	Copyright
Dedication_2018_Circuits--Signals-and-Systems-for-Bioengineers
	Dedication
Preface-to-the-Third-Editio_2018_Circuits--Signals-and-Systems-for-Bioengine
	Preface to the Third Edition
		New to This Edition
		Ancillaries
Acknowledgments_2018_Circuits--Signals-and-Systems-for-Bioengineers
	Acknowledgments
Chapter-1---The-Big-Picture--Bioengineeri_2018_Circuits--Signals-and-Systems
	1. The Big Picture: Bioengineering Signals and Systems
		1.1 Why Biomedical Engineers Need to Analyze Signals and Systems
			1.1.1 Goals of This Book
		1.2 Biosignal: Signals Produced by Living Systems
			1.2.1 Biological Signal Sources
			1.2.2 Biotransducers and Common Physiological Measurements
			1.2.3 Signal Representation: Continuous (Analog) Signals Versus Discrete (Digital) Signals
				1.2.3.1 Analog Signals
				1.2.3.2 Digital Signals
					1.2.3.2.1 Time Sampling
					1.2.3.2.2 Quantization
				1.2.3.3 Time and Frequency Domains
			1.2.4 Two-Dimensional Signals ∼ Images
		1.3 Noise
			1.3.1 Biological Noise Sources
			1.3.2 Noise Properties: Additive Gaussian Noise
				1.3.2.1 Electronic Noise
					1.3.2.1.1 Johnson Noise
					1.3.2.1.2 Shot Noise
		1.4 Biological Systems
			1.4.1 Deterministic Versus Stochastic Signals and Systems
				1.4.1.1 Chaotic Signals and Systems
				1.4.1.2 Fractal Signals and Images
			1.4.2 Deterministic Signal Properties: Periodic, Aperiodic, and Transient
				1.4.2.1 Time-Invariant Versus Nonstationary Signals and Systems
			1.4.3 Causal Versus Noncausal Signals and Systems
			1.4.4 Linear Versus Nonlinear Signals and Systems
			1.4.5 Biosystems Modeling
				1.4.5.1 Analog Models
				1.4.5.2 Systems Models (Transfer Function Models)
		1.5 Summary
		Problems
Chapter-2---Signal-Analysis-in-the-_2018_Circuits--Signals-and-Systems-for-B
	2. Signal Analysis in the Time Domain
		2.1 GOALS OF THIS CHAPTER
		2.2 TIME DOMAIN MEASUREMENTS
			2.2.1 Mean and Root Mean Squared Signal Measurements
				2.2.1.1 Decibels
				2.2.1.2 Signal-to-Noise Ratio
			2.2.2 Variance and Standard Deviation
			2.2.3 Averaging for Noise Reduction
			2.2.4 Ensemble Averaging
		2.3 THE BASIC WAVEFORM: SINUSOIDS
			2.3.1 Sinusoids as Real-Valued Signals
			2.3.2 Complex Representation of Sinusoids
		2.4 TIME DOMAIN ANALYSIS
			2.4.1 Comparison Through Correlation
			2.4.2 Orthogonal Signals and Orthogonality
			2.4.3 Correlations Between Signals
			2.4.4 Shifted Correlations: Cross-correlation
				2.4.4.1 Zero Padding
				2.4.4.2 Cross-correlating Signals Having Different Lengths
			2.4.5 Autocorrelation
			2.4.6 Autocovariance and Cross-covariance
		2.5 SUMMARY
		PROBLEMS
Chapter-3---Signal-Analysis-in-the-Frequency-Doma_2018_Circuits--Signals-and
	3. Signal Analysis in the Frequency Domain: The Fourier Series and the Fourier Transformation
		3.1 GOALS OF THIS CHAPTER
		3.2 TIME–FREQUENCY DOMAINS: GENERAL CONCEPTS
		3.3 TIME–FREQUENCY TRANSFORMATION OF CONTINUOUS SIGNALS
			3.3.1 Sinusoidal Properties in the Time and Frequency Domains
			3.3.2 Sinusoidal Decomposition: The Fourier Series
			3.3.3 Fourier Series Analysis and the Fourier Transform
			3.3.4 Finding the Fourier Coefficients
			3.3.5 Symmetry
			3.3.6 Complex Representation
			3.3.7 The Continuous Fourier Transform
		3.4 TIME–FREQUENCY TRANSFORMATION IN THE DISCRETE DOMAIN
			3.4.1 The Discrete Fourier Transform
			3.4.2 MATLAB Implementation of the Discrete Fourier Transform
			3.4.3 Details of the DFT Spectrum
				3.4.3.1 DFT Spectral Redundancy
				3.4.3.2 Phase Wrapping
				3.4.3.3 The Effect of Time Shifts on the Fourier Transform
				3.4.3.4 Respiratory Example
			3.4.4 The Inverse Discrete Fourier Transform
		3.5 SUMMARY
		PROBLEMS
Chapter-4---Signal-Analysis-in-the-Frequency-_2018_Circuits--Signals-and-Sys
	4. Signal Analysis in the Frequency Domain—Implications and Applications
		4.1 GOALS OF THIS CHAPTER
		4.2 DATA ACQUISITION AND STORAGE
			4.2.1 Data Sampling: The Sampling Theorem
			4.2.2 Amplitude Slicing—Quantization
			4.2.3 Data Truncation
				4.2.3.1 Data Length and Spectral Resolution
			4.2.4 Data Truncation—Window Functions
		4.3 POWER SPECTRUM
		4.4 SPECTRAL AVERAGING
		4.5 SIGNAL BANDWIDTH
		4.6 TIME–FREQUENCY ANALYSIS
		4.7 SUMMARY
		PROBLEMS
Chapter-5---Linear-Systems-Analysis-in-the_2018_Circuits--Signals-and-System
	5. Linear Systems Analysis in the Time Domain—Convolution
		5.1 GOALS OF THIS CHAPTER
		5.2 LINEAR SYSTEMS ANALYSIS—AN OVERVIEW
			5.2.1 Superposition and Linearity
		5.3 A SLICE IN TIME: THE IMPULSE SIGNAL
			5.3.1 Real-World Impulse Signals
			5.3.2 The Impulse Signal in the Frequency Domain
		5.4 USING THE IMPULSE RESPONSE TO FIND A SYSTEMS OUTPUT TO ANY INPUT—CONVOLUTION
			5.4.1 Finding the Impulse Response
			5.4.2 MATLAB Implementation
		5.5 APPLIED CONVOLUTION—BASIC FILTERS
		5.6 CONVOLUTION IN THE FREQUENCY DOMAIN
			5.6.1 Data Sampling Revisited
		5.7 SUMMARY
		PROBLEMS
Chapter-6---Linear-Systems-in-the-Frequency_2018_Circuits--Signals-and-Syste
	6. Linear Systems in the Frequency Domain: The Transfer Function
		6.1 Goals of This Chapter
		6.2 Systems Analysis Models
		6.3 The Response of System Elements to Sinusoidal Inputs: Phasor Analysis
		6.4 The Transfer Function
			6.4.1 The Spectrum of a Transfer Function
		6.5 The Spectrum of System Elements: The Bode Plot
			6.5.1 Constant Gain Element
			6.5.2 Derivative Element
			6.5.3 Integrator Element
			6.5.4 First-Order Element
			6.5.5 Second-Order Element
		6.6 Bode Plots Combining Multiple Elements
			6.6.1 Constructing the Transfer Function From the System Spectrum
		6.7 The Transfer Function and the Fourier Transform
		6.8 Summary
		Problems
Chapter-7---Linear-Systems-in-the-Complex-Fre_2018_Circuits--Signals-and-Sys
	7. Linear Systems in the Complex Frequency Domain: The Laplace Transform
		7.1 GOALS OF THIS CHAPTER
		7.2 THE LAPLACE TRANSFORM
			7.2.1 Definition of the Laplace Transform
			7.2.2 Calculus Operations in the Laplace Domain
			7.2.3 Sources—Common Signals in the Laplace Domain
			7.2.4 Converting the Laplace Transform to the Frequency Domain
			7.2.5 The Inverse Laplace Transform
		7.3 THE LAPLACE DOMAIN TRANSFER FUNCTION
			7.3.1 Time Delay Element: The Time Delay Theorem
			7.3.2 Constant Gain Element
			7.3.3 Derivative Element
			7.3.4 Integrator Element
			7.3.5 First-Order Element
				7.3.5.1 The Characteristic Equation
			7.3.6 Second-Order Element
				7.3.6.1 Second-Order Elements With Real Roots
				7.3.6.2 Partial Fraction Expansion—Manual Methods
				7.3.6.3 Partial Fraction Expansion—MATLAB
				7.3.6.4 Second-Order Processes With Complex Roots
			7.3.7 Higher-Order Transfer Functions
		7.4 NONZERO INITIAL CONDITIONS—INITIAL AND FINAL VALUE THEOREMS
			7.4.1 Nonzero Initial Conditions
			7.4.2 Initial and Final Value Theorems
		7.5 THE LAPLACE DOMAIN, THE FREQUENCY DOMAIN, AND THE TIME DOMAIN
		7.6 SYSTEM IDENTIFICATION
		7.7 SUMMARY
		PROBLEMS
Chapter-8---Analysis-of-Discrete-Linear-Systems_2018_Circuits--Signals-and-S
	8. Analysis of Discrete Linear Systems—The z-Transform and Applications to Filters
		8.1 GOALS OF THIS CHAPTER
		8.2 THE Z-TRANSFORM
			8.2.1 The Unit Delay
			8.2.2 The Digital Transfer Function
			8.2.3 Transformation From the z-Domain to the Frequency Domain
		8.3 DIFFERENCE EQUATIONS
		8.4 LINEAR FILTERS—INTRODUCTION
			8.4.1 Filter Properties
				8.4.1.1 Filter Bandwidth
				8.4.1.2 Filter Type
				8.4.1.3 Filter Attenuation Slope—Filter Order
				8.4.1.4 Filter Initial Sharpness
			8.4.2 Finite Impulse Response Versus Infinite Impulse Response Filter Characteristics
			8.4.3 Causal and Noncausal Filters
		8.5 DESIGN OF FINITE IMPULSE RESPONSE FILTERS
			8.5.1 Derivative Filters—The Two-Point Central Difference Algorithm
			8.5.2 Determining Cutoff Frequency and Skip Factor
		8.6 FINITE IMPULSE RESPONSE AND INFINITE IMPULSE RESPONSE FILTER DESIGN USING THE SIGNAL PROCESSING TOOLBOX
			8.6.1 Finite Impulse Response Filter design
			8.6.2 Designing Infinite Impulse Response Filters
		8.7 SUMMARY
		PROBLEMS
Chapter-9---System-Simulation-and-_2018_Circuits--Signals-and-Systems-for-Bi
	9. System Simulation and Simulink
		9.1 Goals of This Chapter
		9.2 Digital Simulation of Continuous Systems
		9.3 Introduction to Simulink
			9.3.1 Model Specification and Simulation
			9.3.2 Complex System Simulations
		9.4 Improving Control System Performance: The PID controller
		9.5 Biological Examples
			9.5.1 Stolwijk–Hardy Model of Glucose–Insulin Concentrations
			9.5.2 Model of the Neuromuscular Motor Reflex
			9.5.3 The Makay and Glass Model of Neutrophil Density
		9.6 Summary
		Problems
Chapter-10---Stochastic--Nonstationary--and_2018_Circuits--Signals-and-Syste
	10. Stochastic, Nonstationary, and Nonlinear Systems and Signals
		10.1 Goals of This Chapter
		10.2 Stochastic Processes: Stationarity and Ergodicity
		10.3 Signal Nonlinearity
			10.3.1 Fractal Dimension
				10.3.1.1 State Variables and State Space
				10.3.1.2 Delay Embedding
				10.3.1.3 Correlation Dimension
			10.3.2 Information-Based Methods
				10.3.2.1 Sample Entropy
				10.3.2.2 Multiscale Entropy
					10.3.2.2.1 Data Scaling Through Coarse Graining
			10.3.3 Detrended Fluctuation Analysis
		10.4 Summary
		Problems
		Detrended Fluctuation Analysis
Chapter-11---Two-Dimensional-Signals-Ba_2018_Circuits--Signals-and-Systems-f
	11. Two-Dimensional Signals—Basic Image Analysis
		11.1 Goals of This Chapter
		11.2 Image Format and Display
		11.3 The Two-Dimensional Fourier Transform
			11.3.1 MATLAB Implementation
		11.4 Linear Filtering
			11.4.1 Convolution in Two Dimensions
			11.4.2 Linear Image Filters
			11.4.3 Linear Filter Application
		11.5 Image Segmentation
			11.5.1 Pixel-Based Methods
				11.5.1.1 Threshold Level Adjustment
			11.5.2 Edge Detection
			11.5.3 Continuity-Based Methods
				11.5.3.1 Texture Analysis and Nonlinear Filtering
		11.6 Summary
		Problems
Chapter-12---Circuit-Elements-and-Cir_2018_Circuits--Signals-and-Systems-for
	12. Circuit Elements and Circuit Variables
		12.1 Goals of This Chapter
		12.2 System Variables: The Signals of Electrical and Mechanical Systems
			12.2.1 Electrical and Mechanical Variables
			12.2.2 Voltage and Current Definitions
		12.3 Analog System Versus General Systems
		12.4 Electrical Elements
			12.4.1 Passive Electrical Elements
				12.4.1.1 Energy Users: Resistors
				12.4.1.2 Energy Storage Devises: Inductors and Capacitors
					12.4.1.2.1 Inductor
					12.4.1.2.2 Capacitor
				12.4.1.3 Electrical Elements: Reality Check
			12.4.2 Electrical Elements: Active Elements or Sources
			12.4.3 The Fluid Analogy
		12.5 Phasor Analysis
			12.5.1 Phasor Representation—Electrical Elements
		12.6 Laplace Domain—Electrical Elements
			12.6.1 Electrical Elements With Zero Initial Conditions
			12.6.2 Nonzero Initial Conditions
		12.7 Summary: Electrical Elements
		12.8 Mechanical Elements
			12.8.1 Passive Mechanical Elements
			12.8.2 Elasticity
			12.8.3 Mechanical Sources
			12.8.4 Phasor Analysis of Mechanical Systems: Mechanical Impedance
			12.8.5 Laplace Domain Representations of Mechanical Elements With Nonzero Initial Conditions
		12.9 Summary
		Problems
Chapter-13---Analysis-of-Analog-Circu_2018_Circuits--Signals-and-Systems-for
	13. Analysis of Analog Circuits and Models
		13.1 Goals of This Chapter
		13.2 Conservation Laws: Kirchhoff's Voltage Law
			13.2.1 Mesh Analysis: Single Loops
			13.2.2 Mesh Analysis: Multiple Loops
				13.2.2.1 Shortcut Method for Multimesh Circuits
			13.2.3 Mesh Analysis: MATLAB Implementation
		13.3 Conservation Laws: Kirchhoff's Current Law—Nodal Analysis
		13.4 Conservation Laws: Newton's Law—Mechanical Systems
		13.5 Resonance
			13.5.1 Resonant Frequency
			13.5.2 Resonant Bandwidth, Q
		13.6 Summary
		Problems
Chapter-14---Circuit-Reduction--Simp_2018_Circuits--Signals-and-Systems-for-
	14. Circuit Reduction: Simplifications
		14.1 Goals of the Chapter
		14.2 System Simplifications—Passive Network Reduction
			14.2.1 Series Electrical Elements
			14.2.2 Parallel Elements
				14.2.2.1 Combining Two Parallel Impedances
		14.3 Network Reduction—Passive Networks
			14.3.1 Network Reduction—Successive Series–Parallel Combination
				14.3.1.1 Resonance Revisited
			14.3.2 Network Reduction—Voltage–Current Method
		14.4 Ideal and Real Sources
			14.4.1 The Voltage–Current or v–i Plot
			14.4.2 Real Voltage Sources—The Thévenin Source
			14.4.3 Real Current Sources
			14.4.4 Thévenin and Norton Circuit Conversion
		14.5 Thévenin and Norton Theorems: Network Reduction With Sources
		14.6 Measurement Loading
			14.6.1 Ideal and Real Measurement Devices
			14.6.2 Maximum Power Transfer
		14.7 Mechanical Systems
		14.8 Multiple Sources—Revisited
		14.9 Summary
		Problems
Chapter-15---Basic-Analog-Electronics--O_2018_Circuits--Signals-and-Systems-
	15. Basic Analog Electronics: Operational Amplifiers
		15.1 Goals of This Chapter
		15.2 The Amplifier
		15.3 The Operational Amplifier
		15.4 The Noninverting Amplifier
		15.5 The Inverting Amplifier
		15.6 Practical Op Amps
			15.6.1 Limitations in Transfer Characteristics of Real Operational Amplifiers
				15.6.1.1 Bandwidth
				15.6.1.2 Stability
			15.6.2 Input Characteristics
				15.5.2.1 Input Voltage Sources
				15.6.2.2 Input Current Sources
				15.6.2.3 Input Impedance
			15.6.3 Output Characteristics
		15.7 Power Supply
		15.8 Operational Amplifier Circuits or 101 Things to Do With an Operational Amplifier
			15.8.1 The Differential Amplifier
			15.8.2 The Adder
			15.8.3 The Buffer Amplifier
			15.8.4 The Transconductance Amplifier5
			15.8.5 Analog Filters
			15.8.6 Instrumentation Amplifier
		15.9 Summary
		Problems
Appendix-A---Derivations_2018_Circuits--Signals-and-Systems-for-Bioengineers
	A - Derivations
Appendix-B---Laplace-Transforms-and-Propert_2018_Circuits--Signals-and-Syste
	B - Laplace Transforms and Properties of the Fourier Transform
Appendix-C---Trigonometric-and-Othe_2018_Circuits--Signals-and-Systems-for-B
	C - Trigonometric and Other Formulae
Appendix-D---Conversion-Factors-_2018_Circuits--Signals-and-Systems-for-Bioe
	D - Conversion Factors: Units
Appendix-E---Complex-Arithmet_2018_Circuits--Signals-and-Systems-for-Bioengi
	E - Complex Arithmetic
Appendix-F---LF356-Specificati_2018_Circuits--Signals-and-Systems-for-Bioeng
	F - LF356 Specifications
Appendix-G---Determinants-and-Cram_2018_Circuits--Signals-and-Systems-for-Bi
	G - Determinants and Cramer's Rule
Bibliography_2018_Circuits--Signals-and-Systems-for-Bioengineers
	Bibliography
Index_2018_Circuits--Signals-and-Systems-for-Bioengineers
	Index
		A
		B
		C
		D
		E
		F
		G
		H
		I
		J
		K
		L
		M
		N
		O
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		Q
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		U
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		X
		Y
		Z