Signals and systems using MATLAB /

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This new textbook in Signals and Systems provides a pedagogically-rich approach to what can oftentimes be a mathematically 'dry' subject. Chaparro introduces both continuous and discrete time systems, then covers each separately in depth. Careful explanations of each concept are paired wit...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Chaparro, Luis F. (Autor)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Burlington, MA : Academic Press, �2011.
Temas:
MATLAB.
Signal processing > Digital techniques.
System analysis.
Systems Analysis
Traitement du signal > Techniques num�eriques.
Analyse de syst�emes.
systems analysis.
COMPUTERS > Information Theory.
TECHNOLOGY & ENGINEERING > Signals & Signal Processing.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • From the Ground Up; Continuous-time Signals; Continuous-time Systems; The Laplace Transform; Frequency Analysis: The Fourier Series; Frequency Analysis: The Fourier Transform; Application to Control and Communications; Sampling Theory; Discrete-time Signals and Systems; The Z-transform; Fourier Representation of Discrete-time Signals and Systems; Introduction to Discrete Filtering; Applications of Discrete-time Signals and Systems; Appendix A: Useful Formulas.
  • Part 1. Introduction
  • Chapter 0. From the Ground Up!
  • 0.1. Signals and Systems and Digital Technologies
  • 0.2. Examples of Signal Processing Applications
  • 0.2.1. Compact-Disc Player
  • 0.2.2. Software-Defined Radio and Cognitive Radio
  • 0.2.3. Computer-Controlled Systems
  • 0.3. Analog or Discrete?
  • 0.3.1. Continuous-Time and Discrete-Time Representations
  • 0.3.2. Derivatives and Finite Differences
  • 0.3.3. Integrals and Summations
  • 0.3.4. Differential and Difference Equations
  • 0.4. Complex or Real?
  • 0.4.1. Complex Numbers and Vectors
  • 0.4.2. Functions of a Complex Variable
  • 0.4.3. Phasors and Sinusoidal Steady State
  • 0.4.4. Phasor Connection
  • 0.5. Soft Introduction to MATLAB
  • 0.5.1. Numerical Computations
  • 0.5.2. Symbolic Computations
  • Problems
  • Part 2. Theory and Application of Continuous-Time Signals and Systems
  • Chapter 1. Continous-Time Signals
  • 1.1. Introduction
  • 1.2. Classification of Time-Dependent Signals
  • 1.3. Continuous-Time Signals
  • 1.3.1. Basic Signal Operations---Time Shifting and Reversal
  • 1.3.2. Even and Odd Signals
  • 1.3.3. Periodic and Aperiodic Signals
  • 1.3.4. Finite-Energy and Finite Power Signals
  • 1.4. Representation Using Basic Signals
  • 1.4.1. Complex Exponentials
  • 1.4.2. Unit-Step, Unit-Impulse, and Ramp Signals
  • 1.4.3. Special Signals---the Sampling Signal and the Sinc
  • 1.4.4. Basic Signals Operations---Time Scaling, Frequency Shifting, and Windowing
  • 1.4.5. Generic Representation of Signals
  • 1.5. What Have We Accomplished? Where do we Go from Here?
  • Problems
  • Chapter 2. Continuous-Time Systems
  • 2.1. Introduction
  • 2.2. System Concept
  • 2.2.1. System Classification
  • 2.3. LTI Continuous-Time Systems
  • 2.3.1. Linearity
  • 2.3.2. Time Invariance
  • 2.3.3. Representation of Systems by Differential Equations
  • 2.3.4. Application of Superposition and Time Invariance
  • 2.3.5. Convolution Integral
  • 2.3.6. Causality
  • 2.3.7. Graphical Computation of Convolution Integral
  • 2.3.8. Interconnection of Systems---Block Diagrams
  • 2.3.9. Bounded-Input Bounded-Output Stability
  • 2.4. What have We Accomplished? Where Do We Go from Here?
  • Problems
  • Chapter 3. The laplace Transform
  • 3.1. Introduction
  • 3.2. The Two-Sided Laplace Transform
  • 3.2.1. Eigenfunctions of LTI Systems
  • 3.2.2. Poles and Zeros and Region of Convergence
  • 3.3. The One-Sided Laplace Transform
  • 3.3.1. Linearity
  • 3.3.2. Differentiation
  • 3.3.3. Integration
  • 3.3.4. Time Shifting
  • 3.3.5. Convolution Integral
  • 3.4. Inverse Laplace Transform
  • 3.4.1. Inverse of One-Sided Laplace Transforms
  • 3.4.2. Inverse of Functions Containing e-ps Terms
  • 3.4.3. Inverse of Two-Sided Laplace Transforms
  • 3.5. Analysis of LTI-Systems
  • 3.5.1. LTI Systems Represented by Ordinary Differential Equations
  • 3.5.2. Computation of the Convolution Integral
  • 3.6. What Have We Accomplished? Where Do We Go from Here?
  • Problems
  • Chapter 4. Frequency Analysis: The Fourier Series
  • 4.1. Introduction
  • 4.2. Eigenfunctions Revisited
  • 4.3. Complex Exponential Fourier Series
  • 4.4. Line Spectra
  • 4.4.1. Parseval's Theorem---Power Distribution over Frequency
  • 4.4.2. Symmetry of Line Spectra
  • 4.5. Trigonometric Fourier Series
  • 4.6. Fourier Coefficients from Laplace
  • 4.7. Convergence of the Fourier Series
  • 4.8. Time and Frequency Shifting
  • 4.9. Response of LTI Systems to Periodic Signals
  • 4.9.1. Sinusoidal Steady State
  • 4.9.2. Filtering of Periodic Signals
  • 4.10. Other Properties of the Fourier Series
  • 4.10.1. Reflection and Even and Odd Periodic Signals
  • 4.10.2. Linearity of Fourier Series---Addition of Periodic Signals
  • 4.10.3. Multiplicationof Periodic Signals
  • 4.10.4. Derivatives and Integrals of Periodic Signals
  • 4.11. What Have We Accomplished? Where Do We Go from Here?
  • Problems
  • Chapter 5. Frequency Analysis: The Fourier Transform
  • 5.1. Introduction
  • 5.2. From the Fourier Series to the Fourier Transform
  • 5.3. Existence of the Fourier Transform
  • 5.4. Fourier Transforms from the Laplace Transform
  • 5.5. Linearity, Inverse Proportionality, and Duality
  • 5.5.1. Linearity
  • 5.5.2. Inverse Proportionality of Time and Frequency
  • 5.5.3. Duality
  • 5.6. Spectral Representation
  • 5.6.1. Signal Modulation
  • 5.6.2. Fourier Transform of Periodic Signals
  • 5.6.3. Parseval's Energy Conservation
  • 5.6.4. Symmetry of Spectral Representations
  • 5.7. Convolution and Filtering
  • 5.7.1. Basics of Filtering
  • 5.7.2. Ideal Filters
  • 5.7.3. Frequency Response from Poles and Zeros
  • 5.7.4. Spectrum Analyzer
  • 5.8. Additonal Properties
  • 5.8.1. Time Shifting
  • 5.8.2. Differentiation and Integration
  • 5.9. What Have We Accomplished? What Is Next?
  • Problems
  • Chapter 6. Application to Control and Communications
  • 6.1. Introduction
  • 6.2. System Connections and Block Diagrams
  • 6.3. Application to Classic Control
  • 6.3.1. Stability and Stabilization
  • 6.3.2. Transient Analysis of First- and Second-Order Control Systems
  • 6.4. Application to Communications
  • 6.4.1. AM with Suppressed Carrier
  • 6.4.2. Commercial AM
  • 6.4.3. AM Single Sideband
  • 6.4.4. Quadrature AM and Frequency-Division Multiplexing
  • 6.4.5. Angle Modulation
  • 6.5. Analog Filtering
  • 6.5.1. Filtering Basics
  • 6.5.2. Butterworth Low-Pass Filter Design
  • 6.5.3. Chebyshev Low-Pass Filter Design
  • 6.5.4. Frequency Transformations
  • 6.5.5. Filter Design with MATLAB
  • 6.6. What Have We Accomplished? What Is Next?
  • Problems
  • Part 3. Theory and Application of Discrete- Time Signals and Systems
  • Chapter 7. Sampling Theory
  • 7.1. Introduction
  • 7.2. Uniform Sampling
  • 7.2.1. Pulse Amplitude Modulation
  • 7.2.2. Ideal Impulse Sampling
  • 7.2.3. Reconstruction of the Original Continuous-Time Signal
  • 7.2.4. Signal Reconstruction from Sinc Interpolation
  • 7.2.5. Sampling Simulation with MATLAB
  • 7.3. The Nyquist-Shannon Sampling Theorem
  • 7.3.1. Sampling of Modulated Signals
  • 7.4. Practical Aspects of Sampling
  • 7.4.1. Sample-and-Hold Sampling
  • 7.4.2. Quantization and Conding
  • 7.4.3. Sampling, Quantizing, and Coding with MATLAB
  • 7.5. What Have We Accomplished? Where Do We Go from Here?
  • Problems
  • Chapter 8. Discrete-Time Signals and Systems
  • 8.1. Introduction
  • 8.2. Discrete-Time Signals
  • 8.2.1. Periodic and Aperiodic Signals
  • 8.2.2. Finite-Energy and Finite-Power Discrete-Time Signals
  • 8.2.3. Even and Odd Signals
  • 8.2.4. Basic Discrete-Time Signals
  • 8.3. Discrete-Time Systems
  • 8.3.1. Recursive and Nonrecursive Discrete-Time Systems
  • 8.3.2. Discrete-Time Systems Represented by Difference Equations
  • 8.3.3. The Convolution Sum
  • 8.3.4. Linear and Nonlinear Filtering with MATLAB
  • 8.3.5. Causality and Stability of Discrete-Time Systems
  • 8.4. What Have We Accomplished? Where Do We Go from Here?
  • Problems
  • Chapter 9. The Z-Transform
  • 9.1. Introduction
  • 9.2. Laplace Transform of Sampled Signals
  • 9.3. Two-Sided Z-Transform
  • 9.3.1. Region of Convergence
  • 9.4. One-Sided Z-Transform
  • 9.4.1. Computing the Z-Transform with Symbolic MATLAB
  • 9.4.2. Signal Behavior and Poles
  • 9.4.3. Convolution Sum and Transfer Function
  • 9.4.4. Interconnection of Discrete-Time Systems
  • 9.4.5. Initial and Final Value Properties
  • 9.5. One-Sided Z-Transform Inverse
  • 9.5.1. Long-Division Method
  • 9.5.2. Partial Fraction Expansion
  • 9.5.3. Inverse Z-Transform with MATLAB
  • 9.5.4. Solution of Difference Equations
  • 9.5.5. Inverse of Two-Sided Z-Transforms
  • 9.6. What Have We Accomplished? Where Do We Go from Here?
  • Problems
  • Chapter 10. Fourier Analysis of Discrete-Time Signals and Systems
  • 10.1. Introduction
  • 10.2. Discrete-Time Fourier Transform
  • 10.2.1. Sampling, Z-Transform, Eigenfunctions, and the DTFT
  • 10.2.2. Duality in Time and Frequency
  • 10.2.3. Computation of the DTFT Using MATLAB
  • 10.2.4. Time and Frequency Supports
  • 10.2.5. Parseval's Energy Result
  • 10.2.6. Time and Frequency Shifts
  • 10.2.7. Symmetry
  • 10.2.8. Convolution Sum
  • 10.3. Fourier Series of Discrete-Time Periodic Signals
  • 10.3.1. Complex Exponential Discrete Fourier Series
  • 10.3.2. Connection with the Z-Transform.

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