{"product_id":"practical-signals-theory-with-matlab-applications-isbn-9781394266555","title":"Practical Signals Theory with MATLAB Applications","description":"\u003cp\u003e\u003cb\u003eA hands-on resource designed to teach the mathematics of signals and systems with MATLAB\u003c\/b\u003e \u003c\/p\u003e\u003cp\u003eIn this newly revised second edition of \u003ci\u003ePractical Signals Theory with MATLAB Applications,\u003c\/i\u003e Richard Tervo delivers an articulate presentation of the mathematics underlying real world engineering applications and everyday electronic devices. The new edition provides extended coverage of communication systems—including digital and spread spectrum communications—as well as a new introductory chapter on using MATLAB as a tool to visualize the mathematics of signals and systems. \u003c\/p\u003e\u003cp\u003eThe text contains numerous hands-on examples and expanded end-of-chapter exercises. It is a one-stop reference for signals and systems, explaining aspects of commonplace signal types, orthogonality and signal decomposition, transformations, and the graphical presentation of calculations and results.  Readers will also find: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eA solid introduction to the mathematics of continuous and discrete signals represented in time and frequency domains\u003c\/li\u003e \u003cli\u003eThorough coverage of the classic Fourier, Laplace and z-transforms, and their many applications\u003c\/li\u003e \u003cli\u003eNew end-of-chapter worked exercises, a variety of in-line study questions with answers and easily reproducible MATLAB code demonstrations\u003c\/li\u003e \u003cli\u003eBonus material on related applications in different fields of study and a companion website designed to support additional learning\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003ePerfect for undergraduate and graduate students of signals and systems, signals theory, and related areas of electrical engineering,\u003ci\u003ePractical Signals Theory with MATLAB Applications\u003c\/i\u003e will also benefit researchers and professors in the field of system design and signal processing. \u003c\/p\u003e\u003cp\u003ePreface\u003c\/p\u003e \u003cp\u003ePedagogy\u003c\/p\u003e \u003cp\u003eOrganization\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1.\u003c\/b\u003e Practical MATLAB with Signals Theory\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2.\u003c\/b\u003e Introduction to Signals and Systems\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3.\u003c\/b\u003e Classification of Signals\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4.\u003c\/b\u003e Linear Systems\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5.\u003c\/b\u003e The Fourier Series\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6.\u003c\/b\u003e The Fourier Transform\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7.\u003c\/b\u003e Practical Fourier Transforms\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8.\u003c\/b\u003e The Laplace Transform\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9.\u003c\/b\u003e Discrete Signals\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10.\u003c\/b\u003e The z-Transform             \u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11.\u003c\/b\u003e Communications Systems     \u003c\/p\u003e \u003cp\u003e0.1 Useful Information (inside cover \/ endpaper)  \u003c\/p\u003e \u003cp\u003e0.1.1 Identities             \u003c\/p\u003e \u003cp\u003e0.1.2 Definite Integrals           \u003c\/p\u003e \u003cp\u003e0.1.3 Infinite Series\u003c\/p\u003e \u003cp\u003e0.1.4 Orthogonality\u003c\/p\u003e \u003cp\u003e0.1.5 Signal Inner Product\u003c\/p\u003e \u003cp\u003e0.1.6 Convolution\u003c\/p\u003e \u003cp\u003e0.1.7 Fourier Series\u003c\/p\u003e \u003cp\u003e0.1.8 Complex Fourier Series\u003c\/p\u003e \u003cp\u003e0.1.9 Fourier Transform\u003c\/p\u003e \u003cp\u003e0.1.10 Laplace Transform\u003c\/p\u003e \u003cp\u003e0.1.11 z-Transform\u003c\/p\u003e \u003cp\u003e0.2 List of Acronyms\u003c\/p\u003e \u003cp\u003e0.2.1 Communications Acronyms  \u003c\/p\u003e \u003cp\u003e1 Practical MATLAB with Signals Theory 1\u003c\/p\u003e \u003cp\u003eLearning Objectives\u003c\/p\u003e \u003cp\u003e1.1 Introduction\u003c\/p\u003e \u003cp\u003e1.1.1 Accessing MATLAB\u003c\/p\u003e \u003cp\u003e1.1.2 Learning MATLAB\u003c\/p\u003e \u003cp\u003e1.1.3 The MATLAB Desktop\u003c\/p\u003e \u003cp\u003e1.1.4 Help with MATLAB\u003c\/p\u003e \u003cp\u003e1.1.5 Numeric Variables for Signals Theory\u003c\/p\u003e \u003cp\u003e1.1.6 MATLAB Arrays, Matrices, Vectors\u003c\/p\u003e \u003cp\u003e1.1.7 Recording a MATLAB session\u003c\/p\u003e \u003cp\u003e1.2 Visualizing Functions\u003c\/p\u003e \u003cp\u003e1.2.1 Making a Rough Sketch of a Function\u003c\/p\u003e \u003cp\u003e1.2.2 Plotting a Function by Hand\u003c\/p\u003e \u003cp\u003e1.2.3 Plotting a Function with MATLAB\u003c\/p\u003e \u003cp\u003e1.2.4 Enhanced Plotting Functions\u003c\/p\u003e \u003cp\u003e1.3 MATLAB M-Files\u003c\/p\u003e \u003cp\u003e1.3.1 Creating a MATLAB Function\u003c\/p\u003e \u003cp\u003e1.3.2 Anonymous Functions\u003c\/p\u003e \u003cp\u003e1.4 Numerical Integration\u003c\/p\u003e \u003cp\u003e1.4.1 Generalized Numerical Integration\u003c\/p\u003e \u003cp\u003e1.5 The for loop\u003c\/p\u003e \u003cp\u003e1.6 Conditional and Logical Expressions\u003c\/p\u003e \u003cp\u003e1.7 Piecewise Continuous Signals\u003c\/p\u003e \u003cp\u003e1.8 Complex Numbers in MATLAB\u003c\/p\u003e \u003cp\u003e1.8.1 Representation of Complex Numbers\u003c\/p\u003e \u003cp\u003e1.8.2 Euler's Formula\u003c\/p\u003e \u003cp\u003e1.8.3 The Complex Plane\u003c\/p\u003e \u003cp\u003eViewing a Function from Different Perspectives\u003c\/p\u003e \u003cp\u003e1.9 Conclusions\u003c\/p\u003e \u003cp\u003e1.10 Worked Problems\u003c\/p\u003e \u003cp\u003e1.11 End of Chapter Exercises\u003c\/p\u003e \u003cp\u003eBibliography\u003c\/p\u003e \u003cp\u003e2 Introduction to Signals and Systems\u003c\/p\u003e \u003cp\u003eLearning Objectives\u003c\/p\u003e \u003cp\u003e2.1 Introduction\u003c\/p\u003e \u003cp\u003e2.1.1 What is a Signal?\u003c\/p\u003e \u003cp\u003e2.1.2 What is a System?\u003c\/p\u003e \u003cp\u003e2.2 Introduction to Signal Manipulation\u003c\/p\u003e \u003cp\u003e2.2.1 Amplification\u003c\/p\u003e \u003cp\u003e2.2.2 Shifting\u003c\/p\u003e \u003cp\u003e2.2.3 Scaling\u003c\/p\u003e \u003cp\u003e2.2.4 Linear Combination\u003c\/p\u003e \u003cp\u003e2.2.5 Addition and Multiplication of Signals\u003c\/p\u003e \u003cp\u003e2.2.6 Visualizing Signals - An Important Skill\u003c\/p\u003e \u003cp\u003e2.3 Basic Signals\u003c\/p\u003e \u003cp\u003e2.3.1 The Unit Rectangle : rect(t)\u003c\/p\u003e \u003cp\u003e2.3.2 The Unit Step u(t)\u003c\/p\u003e \u003cp\u003e2.3.3 The Exponential e\u003csup\u003ekt\u003c\/sup\u003e \u003c\/p\u003e \u003cp\u003e2.3.4 The Unit Impulse δ(t)\u003c\/p\u003e \u003cp\u003e2.3.5 Plotting the Impulse Aδ(t-x)\u003c\/p\u003e \u003cp\u003e2.4 The Sinusoidal Signal\u003c\/p\u003e \u003cp\u003e2.4.1 The One-Sided Cosine Representation\u003c\/p\u003e \u003cp\u003e2.4.2 Phase Change -\u003c\/p\u003e \u003cp\u003ePhase Change vs. Time Shift\u003c\/p\u003e \u003cp\u003e2.4.3 Sine vs. Cosine\u003c\/p\u003e \u003cp\u003e2.5 Conclusions\u003c\/p\u003e \u003cp\u003e2.6 Worked Problems\u003c\/p\u003e \u003cp\u003e2.7 End of Chapter Exercises\u003c\/p\u003e \u003cp\u003eBibliography\u003c\/p\u003e \u003cp\u003e3 Classification of Signals\u003c\/p\u003e \u003cp\u003eLearning Objectives\u003c\/p\u003e \u003cp\u003e3.1 Introduction\u003c\/p\u003e \u003cp\u003e3.2 Odd and Even Signals\u003c\/p\u003e \u003cp\u003e3.2.1 Combining Odd and Even signals\u003c\/p\u003e \u003cp\u003e3.2.2 The constant value s(t) = k\u003c\/p\u003e \u003cp\u003e3.3 Periodic Signals\u003c\/p\u003e \u003cp\u003e3.3.1 DC Component in Periodic Signals\u003c\/p\u003e \u003cp\u003e3.3.2 Sinusoids and Rectifiers\u003c\/p\u003e \u003cp\u003e3.3.3 Square Wave\u003c\/p\u003e \u003cp\u003e3.3.4 Sawtooth Wave\u003c\/p\u003e \u003cp\u003e3.3.5 Triangle wave\u003c\/p\u003e \u003cp\u003e3.3.6 Pulse Train\u003c\/p\u003e \u003cp\u003e3.3.7 Rectangular Pulse Train\u003c\/p\u003e \u003cp\u003e3.3.8 Impulse Train\u003c\/p\u003e \u003cp\u003e3.3.9 Trigonometric Identities\u003c\/p\u003e \u003cp\u003e3.3.10 Sinusoidal Multiplication\u003c\/p\u003e \u003cp\u003eModulation Property\u003c\/p\u003e \u003cp\u003eDial Tone Generator\u003c\/p\u003e \u003cp\u003eSquaring the Sinusoid\u003c\/p\u003e \u003cp\u003e3.4 Energy and Power Signals\u003c\/p\u003e \u003cp\u003e3.4.1 Periodic Signals = Power Signals\u003c\/p\u003e \u003cp\u003eV\u003csub\u003erms\u003c\/sub\u003e is not always A\/√2\u003c\/p\u003e \u003cp\u003e3.4.2 Comparing Signal Power: The Decibel (dB)\u003c\/p\u003e \u003cp\u003e3.5 Complex Signals\u003c\/p\u003e \u003cp\u003e3.6 Discrete Time Signals\u003c\/p\u003e \u003cp\u003e3.7 Random Signals\u003c\/p\u003e \u003cp\u003e3.8 Conclusions\u003c\/p\u003e \u003cp\u003e3.9 Worked Problems\u003c\/p\u003e \u003cp\u003e3.10 End of Chapter Exercises\u003c\/p\u003e \u003cp\u003eBibliography\u003c\/p\u003e \u003cp\u003e4 Linear Systems\u003c\/p\u003e \u003cp\u003eLearning Objectives\u003c\/p\u003e \u003cp\u003e4.1 Introduction\u003c\/p\u003e \u003cp\u003e4.2 Definition of a Linear System\u003c\/p\u003e \u003cp\u003e4.2.1 Superposition\u003c\/p\u003e \u003cp\u003e4.2.2 Example 1: Zero-State Response\u003c\/p\u003e \u003cp\u003e4.2.3 Example 2: Operating in a linear region\u003c\/p\u003e \u003cp\u003e4.2.4 Example 3: Mixer\u003c\/p\u003e \u003cp\u003e4.2.5 Linear Time-Invariant (LTI) Systems\u003c\/p\u003e \u003cp\u003e4.2.6 Bounded Input, Bounded Output\u003c\/p\u003e \u003cp\u003e4.2.7 System Behavior as a Black Box\u003c\/p\u003e \u003cp\u003e4.3 LTI System Response Function h(t)\u003c\/p\u003e \u003cp\u003e4.4 Convolution\u003c\/p\u003e \u003cp\u003e4.4.1 The Convolution Integral\u003c\/p\u003e \u003cp\u003e4.4.2 Convolution is Commutative\u003c\/p\u003e \u003cp\u003e4.4.3 Convolution is Associative\u003c\/p\u003e \u003cp\u003e4.4.4 Convolution is Distributive over Addition\u003c\/p\u003e \u003cp\u003e4.4.5 Evaluation of the Convolution Integral\u003c\/p\u003e \u003cp\u003eGraphical Convolution 1: Rectangle with Itself\u003c\/p\u003e \u003cp\u003e4.4.6 Convolution Properties\u003c\/p\u003e \u003cp\u003eGraphical Convolution 2: Two Rectangles\u003c\/p\u003e \u003cp\u003eGraphical Convolution 3: Rectangle and Exponential Decay\u003c\/p\u003e \u003cp\u003e4.4.7 Convolution in MATLAB\u003c\/p\u003e \u003cp\u003e4.5 Determining h(t) in an Unknown System\u003c\/p\u003e \u003cp\u003e4.5.1 The Unit Impulse δ(t) Test Signal\u003c\/p\u003e \u003cp\u003e4.5.2 Convolution and Signal Decomposition\u003c\/p\u003e \u003cp\u003eConvolution and Periodic Signals\u003c\/p\u003e \u003cp\u003e4.5.3 An Ideal Distortionless System\u003c\/p\u003e \u003cp\u003eDeconvolution\u003c\/p\u003e \u003cp\u003e4.6 Causality\u003c\/p\u003e \u003cp\u003e4.6.1 Causality and Zero Input Response\u003c\/p\u003e \u003cp\u003e4.7 Combined Systems\u003c\/p\u003e \u003cp\u003e4.8 Convolution and Random Numbers\u003c\/p\u003e \u003cp\u003e4.9 Useful Hints and Help with MATLAB\u003c\/p\u003e \u003cp\u003e4.10 Chapter Summary\u003c\/p\u003e \u003cp\u003e4.11 Conclusions\u003c\/p\u003e \u003cp\u003e4.12 Worked Problems\u003c\/p\u003e \u003cp\u003e4.13 End of Chapter Exercises\u003c\/p\u003e \u003cp\u003eBibliography\u003c\/p\u003e \u003cp\u003e5 The Fourier Series\u003c\/p\u003e \u003cp\u003eLearning Objectives\u003c\/p\u003e \u003cp\u003eChapter Overview\u003c\/p\u003e \u003cp\u003e5.1 Introduction\u003c\/p\u003e \u003cp\u003e5.2 Expressing Signals by Components\u003c\/p\u003e \u003cp\u003e5.2.1 The Spectrum Analyzer\u003c\/p\u003e \u003cp\u003e5.2.2 Approximating a Signal s(t) by Another\u003c\/p\u003e \u003cp\u003e5.2.3 Estimating One Signal by Another\u003c\/p\u003e \u003cp\u003e5.3 Part One - Orthogonal Signals\u003c\/p\u003e \u003cp\u003e5.4 Orthogonality\u003c\/p\u003e \u003cp\u003e5.4.1 An Orthogonal Signal Space\u003c\/p\u003e \u003cp\u003e5.4.2 The Signal Inner Product Formulation\u003c\/p\u003e \u003cp\u003e5.4.3 Complete Set of Orthogonal Signals\u003c\/p\u003e \u003cp\u003e5.4.4 What if a Complete Set is not Present?\u003c\/p\u003e \u003cp\u003e5.4.5 An Orthogonal Set of Signals\u003c\/p\u003e \u003cp\u003e5.5 Part Two - The Fourier Series\u003c\/p\u003e \u003cp\u003e5.5.1 The Orthogonal Signals {sin(2ϖmƒ\u003csub\u003eo\u003c\/sub\u003et); cos(2ϖnƒ\u003csub\u003eo\u003c\/sub\u003et)}\u003c\/p\u003e \u003cp\u003e5.5.2 The Fourier Series - An Orthogonal Set?\u003c\/p\u003e \u003cp\u003e5.6 Computing Fourier Series Components\u003c\/p\u003e \u003cp\u003e5.6.1 Fourier Series Approximation to an Odd Square Wave\u003c\/p\u003e \u003cp\u003e5.6.2 Zero-Frequency (DC) Component\u003c\/p\u003e \u003cp\u003e5.6.3 Fundamental Frequency Component\u003c\/p\u003e \u003cp\u003e5.6.4 Higher Order Components\u003c\/p\u003e \u003cp\u003e5.6.5 Frequency Spectrum of the Square Wave s(t)\u003c\/p\u003e \u003cp\u003e5.7 Odd and Even Square Waves\u003c\/p\u003e \u003cp\u003e5.7.1 The Fourier Series Components of an Even Square Wave\u003c\/p\u003e \u003cp\u003e5.8 Gibb's Phenomenon\u003c\/p\u003e \u003cp\u003e5.9 Setting-Up the Fourier Series Calculation\u003c\/p\u003e \u003cp\u003e5.9.1 Appearance of Pulse Train Frequency Components\u003c\/p\u003e \u003cp\u003e5.10 Some Common Fourier Series\u003c\/p\u003e \u003cp\u003e5.11 Practical Harmonics\u003c\/p\u003e \u003cp\u003e5.11.1 Audio Ampli_er Specs - Total Harmonic Distortion\u003c\/p\u003e \u003cp\u003e5.11.2 The CB Radio Booster\u003c\/p\u003e \u003cp\u003e5.12 Part Three: The Complex Fourier Series\u003c\/p\u003e \u003cp\u003e5.12.1 Not all Signals are Even or Odd\u003c\/p\u003e \u003cp\u003e5.13 The Complex Fourier Series\u003c\/p\u003e \u003cp\u003e5.13.1 Complex Fourier Series - The Frequency Domain\u003c\/p\u003e \u003cp\u003e5.13.2 Comparing the Real and Complex Fourier Series\u003c\/p\u003e \u003cp\u003e5.13.3 Magnitude and Phase\u003c\/p\u003e \u003cp\u003e5.14 Complex Fourier Series Components\u003c\/p\u003e \u003cp\u003e5.14.1 Real Signals and the Complex Fourier Series\u003c\/p\u003e \u003cp\u003e5.14.2 Stretching and Squeezing: Time vs. Frequency\u003c\/p\u003e \u003cp\u003e5.14.3 Shift in Time\u003c\/p\u003e \u003cp\u003e5.14.4 Change in Amplitude\u003c\/p\u003e \u003cp\u003e5.14.5 Power in Periodic Signals\u003c\/p\u003e \u003cp\u003eFind the Total Power in s(t) = Acos(t) + B sin(t)\u003c\/p\u003e \u003cp\u003e5.14.6 Parseval's Theorem for Periodic Signals\u003c\/p\u003e \u003cp\u003e5.15 Properties of the Complex Fourier Series\u003c\/p\u003e \u003cp\u003e5.16 Analysis of a DC Power Supply\u003c\/p\u003e \u003cp\u003e5.16.1 The DC Component\u003c\/p\u003e \u003cp\u003e5.16.2 An AC-DC Converter\u003c\/p\u003e \u003cp\u003e5.16.3 Vrms is always greater than or equal to V\u003csub\u003edc\u003c\/sub\u003e \u003c\/p\u003e \u003cp\u003e5.16.4 Fourier Series: The Full-wave Rectifier\u003c\/p\u003e \u003cp\u003e5.16.5 Complex Fourier series components C\u003csub\u003en\u003c\/sub\u003e \u003c\/p\u003e \u003cp\u003ePower in the Fundamental Frequency 120 Hz\u003c\/p\u003e \u003cp\u003e5.17 The Fourier Series with MATLAB\u003c\/p\u003e \u003cp\u003e5.17.1 Finding Fourier Series Components\u003c\/p\u003e \u003cp\u003eA full-wave rectified cosine (60 Hz)\u003c\/p\u003e \u003cp\u003e5.17.2 Effective use of the Fast Fourier Transform\u003c\/p\u003e \u003cp\u003e5.18 Conclusions\u003c\/p\u003e \u003cp\u003e5.19 Worked Problems\u003c\/p\u003e \u003cp\u003e5.20 End of Chapter Exercises\u003c\/p\u003e \u003cp\u003eBibliography\u003c\/p\u003e \u003cp\u003e6 The Fourier Transform\u003c\/p\u003e \u003cp\u003eLearning Objectives\u003c\/p\u003e \u003cp\u003e6.1 Introduction\u003c\/p\u003e \u003cp\u003e6.1.1 A Fresh Look at the Fourier Series\u003c\/p\u003e \u003cp\u003ePeriodic and Non-Periodic Signals\u003c\/p\u003e \u003cp\u003e6.1.2 Approximating a Non-Periodic Signal Over All Time\u003c\/p\u003e \u003cp\u003e6.1.3 Definition of the Fourier Transform\u003c\/p\u003e \u003cp\u003e6.1.4 Existence of the Fourier Transform\u003c\/p\u003e \u003cp\u003e6.1.5 The Inverse Fourier Transform\u003c\/p\u003e \u003cp\u003e6.2 Properties of the Fourier Transform\u003c\/p\u003e \u003cp\u003e6.2.1 Linearity of the Fourier Transform\u003c\/p\u003e \u003cp\u003e6.2.2 Value of the Fourier transform at the Origin\u003c\/p\u003e \u003cp\u003e6.2.3 Odd and Even Functions and the Fourier Transform\u003c\/p\u003e \u003cp\u003e6.3 The Rectangle Signal\u003c\/p\u003e \u003cp\u003eAlternate Solution\u003c\/p\u003e \u003cp\u003e6.4 The Sinc Function\u003c\/p\u003e \u003cp\u003e6.4.1 Expressing a Function in Terms of sinc(t)\u003c\/p\u003e \u003cp\u003e6.4.2 The Fourier Transform of a General Rectangle\u003c\/p\u003e \u003cp\u003e6.5 Signal Manipulations: Time and Frequency\u003c\/p\u003e \u003cp\u003e6.5.1 Amplitude Variations\u003c\/p\u003e \u003cp\u003e6.5.2 Stretch and Squeeze: The Sinc Function\u003c\/p\u003e \u003cp\u003e6.5.3 The Scaling Theorem\u003c\/p\u003e \u003cp\u003e6.5.4 Testing the Limits\u003c\/p\u003e \u003cp\u003e6.5.5 A Shift in Time\u003c\/p\u003e \u003cp\u003e6.5.6 The Shifting Theorem\u003c\/p\u003e \u003cp\u003e6.5.7 The Fourier Transform of a Shifted Rectangle\u003c\/p\u003e \u003cp\u003eMagnitude of G(ƒ)\u003c\/p\u003e \u003cp\u003ePhase of G(ƒ)\u003c\/p\u003e \u003cp\u003e6.5.8 Impulse Series - The Line Spectrum\u003c\/p\u003e \u003cp\u003e6.5.9 Shifted Impulse δ(ƒ – ƒ\u003csub\u003eo\u003c\/sub\u003e)\u003c\/p\u003e \u003cp\u003e6.5.10 Fourier Transform of a Periodic Signal\u003c\/p\u003e \u003cp\u003e6.6 Fourier Transform Pairs\u003c\/p\u003e \u003cp\u003e6.6.1 The Illustrated Fourier Transform\u003c\/p\u003e \u003cp\u003e6.7 Rapid Changes vs. High Frequencies\u003c\/p\u003e \u003cp\u003e6.7.1 Derivative Theorem\u003c\/p\u003e \u003cp\u003e6.7.2 Integration Theorem\u003c\/p\u003e \u003cp\u003e6.8 Conclusions\u003c\/p\u003e \u003cp\u003e6.9 Worked Problems\u003c\/p\u003e \u003cp\u003e6.10 End of Chapter Exercises\u003c\/p\u003e \u003cp\u003eBibliography\u003c\/p\u003e \u003cp\u003e7 Practical Fourier Transforms 349\u003c\/p\u003e \u003cp\u003e7.1 Introduction\u003c\/p\u003e \u003cp\u003eLearning Objectives\u003c\/p\u003e \u003cp\u003e7.2 Convolution: Time and Frequency\u003c\/p\u003e \u003cp\u003eThe Logarithm Domain\u003c\/p\u003e \u003cp\u003e7.2.1 Simplifying the Convolution Integral\u003c\/p\u003e \u003cp\u003e7.3 Transfer Function of a Linear System\u003c\/p\u003e \u003cp\u003e7.3.1 Impulse Response: The Frequency Domain\u003c\/p\u003e \u003cp\u003e7.3.2 Frequency Response Curve\u003c\/p\u003e \u003cp\u003e7.4 Energy in Signals: Parseval's Theorem for the Fourier Transform\u003c\/p\u003e \u003cp\u003e7.4.1 Energy Spectral Density\u003c\/p\u003e \u003cp\u003e7.5 Data Smoothing and the Frequency Domain\u003c\/p\u003e \u003cp\u003e7.6 Ideal Filters\u003c\/p\u003e \u003cp\u003e7.6.1 The Ideal Low-Pass Filter is not Causal\u003c\/p\u003e \u003cp\u003e7.7 A Real Low-Pass Filter\u003c\/p\u003e \u003cp\u003eMATLAB Example 1: First Order Filter\u003c\/p\u003e \u003cp\u003e7.8 The Modulation Theorem\u003c\/p\u003e \u003cp\u003e7.8.1 A Voice Privacy System\u003c\/p\u003e \u003cp\u003eSpectral Inversion\u003c\/p\u003e \u003cp\u003e7.9 Periodic Signals and the Fourier Transform\u003c\/p\u003e \u003cp\u003e7.9.1 The Impulse Train\u003c\/p\u003e \u003cp\u003e7.9.2 General Appearance of Periodic Signals\u003c\/p\u003e \u003cp\u003e7.9.3 The Fourier Transform of a Square wave\u003c\/p\u003e \u003cp\u003eChanging the Pulse Train Appearance\u003c\/p\u003e \u003cp\u003e7.9.4 Other Periodic Waveforms\u003c\/p\u003e \u003cp\u003e7.10 The Analog Spectrum Analyzer\u003c\/p\u003e \u003cp\u003e7.11 Conclusions\u003c\/p\u003e \u003cp\u003e7.12 Worked Problems\u003c\/p\u003e \u003cp\u003e7.13 End of Chapter Exercises\u003c\/p\u003e \u003cp\u003eBibliography\u003c\/p\u003e \u003cp\u003e8 The Laplace Transform\u003c\/p\u003e \u003cp\u003eLearning Objectives\u003c\/p\u003e \u003cp\u003e8.1 Introduction\u003c\/p\u003e \u003cp\u003e8.2 The Laplace Transform\u003c\/p\u003e \u003cp\u003e8.2.1 The Frequency Term e\u003csup\u003ejwt \u003c\/sup\u003e\u003c\/p\u003e \u003cp\u003e8.2.2 The Exponential Term e\u003csup\u003eσt\u003c\/sup\u003e \u003c\/p\u003e \u003cp\u003e8.2.3 The s-domain\u003c\/p\u003e \u003cp\u003e8.3 Exploring the s-domain\u003c\/p\u003e \u003cp\u003e8.3.1 Poles and Zeros\u003c\/p\u003e \u003cp\u003e8.3.2 A Pole at the origin\u003c\/p\u003e \u003cp\u003e8.3.3 Decaying Exponential\u003c\/p\u003e \u003cp\u003e8.3.4 A Sinusoid\u003c\/p\u003e \u003cp\u003e8.3.5 A Decaying Sinusoid\u003c\/p\u003e \u003cp\u003e8.3.6 An Unstable System\u003c\/p\u003e \u003cp\u003e8.4 Visualizing the Laplace Transform\u003c\/p\u003e \u003cp\u003e8.4.1 First Order Low-pass Filter\u003c\/p\u003e \u003cp\u003e8.4.2 Pole Position Determines Frequency Response\u003c\/p\u003e \u003cp\u003e8.4.3 Second Order Low-pass Filter\u003c\/p\u003e \u003cp\u003e8.4.4 Two-Sided Laplace Transform\u003c\/p\u003e \u003cp\u003e8.4.5 The Bode Diagram\u003c\/p\u003e \u003cp\u003e8.4.6 Calculating the Laplace Transform\u003c\/p\u003e \u003cp\u003e8.4.7 System Analysis in MATLAB\u003c\/p\u003e \u003cp\u003e8.5 Properties of the Laplace Transform\u003c\/p\u003e \u003cp\u003e8.6 Differential Equations\u003c\/p\u003e \u003cp\u003e8.6.1 Solving a Differential Equation\u003c\/p\u003e \u003cp\u003e8.6.2 Transfer Function as Differential Equations\u003c\/p\u003e \u003cp\u003e8.7 Laplace Transform Pairs\u003c\/p\u003e \u003cp\u003e8.7.1 The Illustrated Laplace Transform\u003c\/p\u003e \u003cp\u003e8.8 Circuit Analysis with the Laplace Transform\u003c\/p\u003e \u003cp\u003e8.8.1 Voltage Divider\u003c\/p\u003e \u003cp\u003e8.8.2 A First-Order Low-pass Filter\u003c\/p\u003e \u003cp\u003e8.8.3 A First-Order High-pass Filter\u003c\/p\u003e \u003cp\u003e8.8.4 A Second Order Filter\u003c\/p\u003e \u003cp\u003e8.9 State Variable Analysis\u003c\/p\u003e \u003cp\u003e8.9.1 State Variable Analysis - First Order System\u003c\/p\u003e \u003cp\u003e8.9.2 First Order State Space Analysis with MATLAB\u003c\/p\u003e \u003cp\u003e8.9.3 State Variable Analysis - Second Order System\u003c\/p\u003e \u003cp\u003e8.9.4 Matrix Form of the State Space Equations\u003c\/p\u003e \u003cp\u003e8.9.5 Second Order State Space Analysis with MATLAB\u003c\/p\u003e \u003cp\u003e8.9.6 Differential Equation\u003c\/p\u003e \u003cp\u003e8.9.7 State Space and Transfer Functions with MATLAB\u003c\/p\u003e \u003cp\u003e8.10 Conclusions\u003c\/p\u003e \u003cp\u003e8.11 Worked Problems\u003c\/p\u003e \u003cp\u003e8.12 End of Chapter Exercises\u003c\/p\u003e \u003cp\u003eBibliography\u003c\/p\u003e \u003cp\u003e9 Discrete Signals\u003c\/p\u003e \u003cp\u003e9.1 Introduction\u003c\/p\u003e \u003cp\u003eLearning Objectives\u003c\/p\u003e \u003cp\u003e9.2 Discrete Time vs. Continuous Time Signals\u003c\/p\u003e \u003cp\u003e9.3 A Discrete Time Signal\u003c\/p\u003e \u003cp\u003e9.3.1 Digital Signal Processing\u003c\/p\u003e \u003cp\u003e9.3.2 A Periodic Discrete Time Signal\u003c\/p\u003e \u003cp\u003e9.4 Data Collection and Sampling Rate\u003c\/p\u003e \u003cp\u003e9.4.1 The Selection of a Sampling Rate\u003c\/p\u003e \u003cp\u003e9.4.2 Bandlimited Signal\u003c\/p\u003e \u003cp\u003e9.4.3 Theory of Sampling\u003c\/p\u003e \u003cp\u003e9.4.4 The Sampling Function\u003c\/p\u003e \u003cp\u003e9.4.5 Recovering a Waveform from Samples\u003c\/p\u003e \u003cp\u003e9.4.6 A Practical Sampling Signal\u003c\/p\u003e \u003cp\u003e9.4.7 Minimum Sampling Rate\u003c\/p\u003e \u003cp\u003e9.4.8 Nyquist Sampling Rate\u003c\/p\u003e \u003cp\u003e9.4.9 The Nyquist Sampling Rate is a Theoretical Minimum\u003c\/p\u003e \u003cp\u003e9.4.10 Sampling Rate and Alias Frequency\u003c\/p\u003e \u003cp\u003e9.4.11 Practical Aliasing\u003c\/p\u003e \u003cp\u003e9.4.12 Analysis of Aliasing\u003c\/p\u003e \u003cp\u003e9.4.13 Anti-Alias Filter\u003c\/p\u003e \u003cp\u003e9.5 Introduction to Digital Filtering\u003c\/p\u003e \u003cp\u003e9.5.1 Impulse Response Function\u003c\/p\u003e \u003cp\u003e9.5.2 A Discrete Response Function\u003c\/p\u003e \u003cp\u003e9.5.3 Delay Blocks are a Natural Consequence of Sampling\u003c\/p\u003e \u003cp\u003e9.5.4 General Digital Filtering\u003c\/p\u003e \u003cp\u003e9.5.5 The Fourier Transform of Sampled Signals\u003c\/p\u003e \u003cp\u003e9.5.6 The Discrete Fourier Transform (DFT)\u003c\/p\u003e \u003cp\u003e9.5.7 A Discrete Fourier Series\u003c\/p\u003e \u003cp\u003e9.5.8 Computing the Discrete Fourier Transform (DFT)\u003c\/p\u003e \u003cp\u003e9.5.9 The Fast Fourier Transform (FFT)\u003c\/p\u003e \u003cp\u003e9.6 Illustrative Examples\u003c\/p\u003e \u003cp\u003eThe FFT (fft) and Inverse FFT (ifft)\u003c\/p\u003e \u003cp\u003e9.6.1 FFT and Sample Rate\u003c\/p\u003e \u003cp\u003e9.6.2 Practical DFT Issues\u003c\/p\u003e \u003cp\u003e9.7 Filtering Application with MATLAB\u003c\/p\u003e \u003cp\u003e9.7.1 Fourier Analysis\u003c\/p\u003e \u003cp\u003e9.7.2 System Response\u003c\/p\u003e \u003cp\u003e9.7.3 Check Calculation\u003c\/p\u003e \u003cp\u003e9.8 Conclusions\u003c\/p\u003e \u003cp\u003e9.9 Worked Problems\u003c\/p\u003e \u003cp\u003e9.10 End of Chapter Exercises\u003c\/p\u003e \u003cp\u003eBibliography\u003c\/p\u003e \u003cp\u003e10 The z-Transform 581\u003c\/p\u003e \u003cp\u003e10.1 Introduction\u003c\/p\u003e \u003cp\u003eLearning Objectives\u003c\/p\u003e \u003cp\u003e10.2 The z-Transform\u003c\/p\u003e \u003cp\u003e10.2.1 Fourier Transform, Laplace Transform, z-transform\u003c\/p\u003e \u003cp\u003e10.2.2 Defnition of the z-Transform\u003c\/p\u003e \u003cp\u003e10.2.3 The z-Plane and the Fourier Transform\u003c\/p\u003e \u003cp\u003e10.3 Calculating the z-Transform\u003c\/p\u003e \u003cp\u003e10.3.1 Unit Step u[n]\u003c\/p\u003e \u003cp\u003e10.3.2 Exponential a\u003csup\u003en\u003c\/sup\u003e u[n]\u003c\/p\u003e \u003cp\u003e10.3.3 Sinusoid cos(nω\u003csub\u003eo\u003c\/sub\u003e) u[n] and sin(nω\u003csub\u003eo\u003c\/sub\u003e) u[n]\u003c\/p\u003e \u003cp\u003e10.3.4 Differentiation\u003c\/p\u003e \u003cp\u003e10.3.5 The Effect of Sampling Rate\u003c\/p\u003e \u003cp\u003e10.4 A Discrete Time Laplace Transform\u003c\/p\u003e \u003cp\u003e10.5 Properties of the z-Transform\u003c\/p\u003e \u003cp\u003e10.6 z-Transform Pairs\u003c\/p\u003e \u003cp\u003e10.7 Transfer Function of a Discrete Linear System\u003c\/p\u003e \u003cp\u003e10.8 MATLAB Analysis with the z-transform\u003c\/p\u003e \u003cp\u003e10.8.1 First Order Low-pass Filter\u003c\/p\u003e \u003cp\u003e10.8.2 Pole-zero Plot\u003c\/p\u003e \u003cp\u003e10.8.3 Bode diagram\u003c\/p\u003e \u003cp\u003e10.8.4 Impulse Response\u003c\/p\u003e \u003cp\u003e10.8.5 Calculating Frequency Response\u003c\/p\u003e \u003cp\u003e10.8.6 Pole Position Determines Frequency Response\u003c\/p\u003e \u003cp\u003e10.9 Digital Filtering - FIR Filter\u003c\/p\u003e \u003cp\u003e10.9.1 A One Pole FIR Filter\u003c\/p\u003e \u003cp\u003e10.9.2 A Two Pole FIR Filter\u003c\/p\u003e \u003cp\u003e10.9.3 Higher Order FIR Filters\u003c\/p\u003e \u003cp\u003e10.10Digital Filtering - IIR Filter\u003c\/p\u003e \u003cp\u003e10.10.1A One Pole IIR Filter\u003c\/p\u003e \u003cp\u003e10.10.2 IIR vs. FIR\u003c\/p\u003e \u003cp\u003e10.10.3 Higher Order IIR Filters\u003c\/p\u003e \u003cp\u003e10.10.4 Combining FIR and IIR Filters\u003c\/p\u003e \u003cp\u003e10.11Conclusions\u003c\/p\u003e \u003cp\u003e10.12Worked Problems\u003c\/p\u003e \u003cp\u003e10.13End of Chapter Exercises\u003c\/p\u003e \u003cp\u003e11 Communication Systems\u003c\/p\u003e \u003cp\u003eLearning Objectives\u003c\/p\u003e \u003cp\u003e11.1 Introduction\u003c\/p\u003e \u003cp\u003e11.1.1 A Baseband Signal m(t)\u003c\/p\u003e \u003cp\u003e11.1.2 The need for a Carrier Signal\u003c\/p\u003e \u003cp\u003e11.1.3 A Carrier Signal c(t)\u003c\/p\u003e \u003cp\u003e11.1.4 Modulation Techniques\u003c\/p\u003e \u003cp\u003e11.1.5 The Radio Spectrum\u003c\/p\u003e \u003cp\u003e11.2 Amplitude Modulation\u003c\/p\u003e \u003cp\u003e11.2.1 Double Sideband Transmitted Carrier - (DSB-TC)\u003c\/p\u003e \u003cp\u003e11.2.2 Demodulation of AM DSB-TC Signals\u003c\/p\u003e \u003cp\u003e11.2.3 Graphical Analysis\u003c\/p\u003e \u003cp\u003e11.2.4 AM Demodulation - Diode Detector\u003c\/p\u003e \u003cp\u003e11.2.5 Examples of Diode Detection\u003c\/p\u003e \u003cp\u003e11.3 Suppressed Carrier Transmission\u003c\/p\u003e \u003cp\u003e11.3.1 Demodulation of Single Sideband Signals\u003c\/p\u003e \u003cp\u003e11.3.2 Percent Modulation and Overmodulation\u003c\/p\u003e \u003cp\u003e11.4 Superheterodyne Receiver\u003c\/p\u003e \u003cp\u003e11.4.1 An Experiment with Intermediate Frequency\u003c\/p\u003e \u003cp\u003e11.4.2 When Receivers become Transmitters\u003c\/p\u003e \u003cp\u003e11.4.3 Image Frequency\u003c\/p\u003e \u003cp\u003e11.4.4 Beat Frequency Oscillator\u003c\/p\u003e \u003cp\u003e11.5 Digital Communications\u003c\/p\u003e \u003cp\u003e11.5.1 Modulation Methods\u003c\/p\u003e \u003cp\u003e11.5.2 Morse Code\u003c\/p\u003e \u003cp\u003e11.5.3 Amplitude Shift Keying (ASK)\u003c\/p\u003e \u003cp\u003e11.5.4 Frequency Shift Keying (FSK)\u003c\/p\u003e \u003cp\u003e11.6 Phase Shift Keying (PSK)\u003c\/p\u003e \u003cp\u003e11.6.1 Differential Coding\u003c\/p\u003e \u003cp\u003e11.6.2 Quadrature Amplitude Modulation (QAM)\u003c\/p\u003e \u003cp\u003e11.7 Spread Spectrum Systems\u003c\/p\u003e \u003cp\u003e11.7.1 Introduction\u003c\/p\u003e \u003cp\u003e11.7.2 Pseudorandom Noise\u003c\/p\u003e \u003cp\u003e11.7.3 Encoding Bits in DSSS\u003c\/p\u003e \u003cp\u003e11.7.4 Spectral Properties of a Pseudo-Random Sequence\u003c\/p\u003e \u003cp\u003e11.7.5 Code Division Multiple Access (CDMA)\u003c\/p\u003e \u003cp\u003e11.8 Conclusions\u003c\/p\u003e \u003cp\u003e11.9 Worked Problems\u003c\/p\u003e \u003cp\u003e11.10End of Chapter Exercises\u003c\/p\u003e \u003cp\u003eBibliography\u003c\/p\u003e \u003cp\u003eA Reference Tables\u003c\/p\u003e \u003cp\u003eA.1 Fourier Transform\u003c\/p\u003e \u003cp\u003eA.1.1 Fourier Transform Theorems\u003c\/p\u003e \u003cp\u003eA.2 Laplace Transform\u003c\/p\u003e \u003cp\u003eA.2.1 Laplace Transform Theorems\u003c\/p\u003e \u003cp\u003eA.3 z-Transform\u003c\/p\u003e \u003cp\u003eA.3.1 z-Transform Theorems\u003c\/p\u003e \u003cp\u003eB The Illustrated Fourier Transform\u003c\/p\u003e \u003cp\u003eC The Illustrated Laplace Transform\u003c\/p\u003e \u003cp\u003eD The Illustrated z-Transform\u003c\/p\u003e \u003cp\u003eE MATLAB Reference Guide\u003c\/p\u003e \u003cp\u003eE.1 Defining Signals\u003c\/p\u003e \u003cp\u003eE.1.1 MATLAB Variables\u003c\/p\u003e \u003cp\u003eE.1.2 The Time Axis\u003c\/p\u003e \u003cp\u003eE.1.3 Common Signals\u003c\/p\u003e \u003cp\u003eE.2 Complex Numbers\u003c\/p\u003e \u003cp\u003eE.3 Plot Commands\u003c\/p\u003e \u003cp\u003eE.4 Signal Operations\u003c\/p\u003e \u003cp\u003eE.5 Defining Systems\u003c\/p\u003e \u003cp\u003eE.5.1 System Definition\u003c\/p\u003e \u003cp\u003eE.5.2 System Analysis\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eRichard Tervo, PhD,\u003c\/b\u003e is a retired Professor of Electrical and Computer Engineering at the University of New Brunswick, Canada. For over 30 years, he taught signals and communications courses at the undergraduate and graduate levels. He is an expert in teaching the mathematical foundations of signal behavior.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989835956453,"sku":"NP9781394266555","price":135.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781394266555.jpg?v=1761785626","url":"https:\/\/k12savings.com\/es\/products\/practical-signals-theory-with-matlab-applications-isbn-9781394266555","provider":"K12savings","version":"1.0","type":"link"}