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    Discrete-Time Signal Processing

    ISBN-10: 0131988425
    ISBN-13: 9780131988422
    Author(s): Alan V. Oppenheim, Ronald Schafer, John R. Buck, Wayne Padgett, Mark T. Yoder
    Buy it from: $21.42
    Rent it from: $52.48
    This item will ship on Friday, December 26 .

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    List Price: $229.80
    Edition: 3rd
    Publisher: Prentice Hall PTR
    Binding: Hardcover
    Pages: 1120
    Size: 7.75" wide x 9.50" long x 1.75" tall
    Weight: 4.532
    Language: English

    Previous edition TOC
    Introduction
    Discrete-Time Signals and Systems
    Introduction
    Discrete-time Signals: Sequences
    Discrete-time Systems
    Linear Time-Invariant Systems
    Properties of Linear Time-Invariant Systems
    Linear Constant-Coefficient Difference Equations
    Frequency-Domain Representation of Discrete-Time Signals and Systems
    Representation of Sequence by Fourier Transforms
    Symmetry Properties of the Fourier Transform
    Fourier Transform Theorems
    Discrete-Time Random Signals
    Summary
    The z-Transform
    Introduction
    The z-Transform
    Properties of the Region of Convergence for the z-Transform
    The Inverse z-Transform
    z-Transform Properties
    Summary
    Sampling of Continuous-Time Signals
    Introduction
    Periodic Sampling
    Frequency-Domain Representation of Sampling
    Reconstruction of a Bandlimited Signal from its Samples
    Discrete-Time Processing of Continuous-Time Signals
    Continuous-Time Processing of Discrete-Time Signals
    Changing the Sampling Rate Using Discrete-Time Processing
    Practical Considerations
    Oversampling and Noise Shaping
    Summary
    Transform Analysis of Linear Time-Invariant Systems
    Introduction
    The Frequency Response of LTI Systems
    System Functions for Systems Characterized by Linea
    Frequency Response for Rational System Functions
    Relationship Between Magnitude and Phase
    All-Pass Systems
    Minimum-Phase Systems
    Linear Systems with Generalized Linear Phase
    Summary
    Structures for Discrete-Time Systems
    Introduction
    Block Diagram Representation of Linear Constant-Coefficient Difference Equations
    Signal Flow Graph Representation of Linear Constant-Coefficient Difference Equations
    Basic Structures for IIR Systems
    Transposed Forms
    Basic Network Structures for FIR Systems
    Overview of Finite-Precision Numerical Effects
    The Effects of Coefficient Quantization
    Effects of Roundoff Noise in Digital Filters
    Zero-Input Limit Cycles in Fixed-Point Realizations of IIR Digital Filters
    Summary
    Filter Design Techniques
    Introduction
    Design of Discrete-Time IIR Filters from Continuous-Time Filters
    Design of FIR Filters by Windowing
    Examples of FIR Filter Design by the Kaiser Window Method
    Optimum Approximations of FIR Filters
    Examples of FIR Equiripple Approximation
    Comments on IIR and FIR Digital Filters
    Summary
    The Discrete Fourier Transform
    Introduction
    Representation of Periodic Sequences: the Discrete Fourier Series
    Summary of Properties of the DFS Representation of Periodic Sequences
    The Fourier Transform of Periodic Signals
    Sampling the Fourier Transform
    Fourier Representation of Finite-Duration Sequences: The Discrete-Fourier Transform
    Properties of the Discrete Fourier Transform
    Summary of Properties of the Discrete Fourier Transform
    Linear Convolution Using the Discrete Fourier Transform
    The Discrete Cosine Transform (DCT)
    Summary
    Computation of the Discrete Fourier Transform
    Introduction
    Efficient Computation of the Discrete Fourier Transform
    The Goertzel Algorithm Decimation-in-Time FFT Algorithms
    Decimation-in-Frequency FFT Algorithms
    Practical Considerations Implementation of the DFT Using Convolution
    Summary
    Fourier Analysis of Signals Using the Discrete Fourier Transform
    Introduction
    Fourier Analysis of Signals Using the DFT
    DFT Analysis of Sinusoidal Signals
    The Time-Dependent Fourier Transform
    Block Convolution Using the Time-Dependent Fourier Transform
    Fourier Analysis of Nonstationary Signals
    Fourier Analysis of Stationary Random Signals: the Periodogram
    Spectrum Analysis of Random Signals Using Estimates of the Autocorrelation Sequence
    Summary

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