Digital Signal Processing: Principles, Algorithms, and Applications – John G. Proakis – 3rd Edition


Suitable for a one- or two-semester undergraduate-level electrical engineering, computer engineering, and computer science course in Discrete Systems and Digital Signal Processing. Assumes some prior knowledge of advanced calculus, linear systems for continuous-time signals, and Fourier series and transforms. Giving students a sound balance of theory and practical application, this no-nonsense text presents the fundamental concepts and techniques of modern digital signal processing with related algorithms and applications.

Covering both time-domain and frequency- domain methods for the analysis of linear, discrete-time systems, the book offers cutting-edge coverage on such topics as sampling, digital filter design, filter realizations, deconvolution, interpolation, decimation, state-space methods, spectrum analysis, and more. Rigorous and challenging, it further prepares students with numerous examples, exercises, and experiments emphasizing software implementation of digital signal processing algorithms integrated throughout.

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  • 1 Introduction
    1.1 Signals, Systems, and Signal Processing
    1.2 Classification of Signals
    1.3 The Concept of Frequency in Continuous-Time and Discrete-Time Signals
    1.4 Analog-to-Digital and Digital-to-Analog Conversion
    1.5 Summary and References
    2 Discrete-Time Signals And Systems
    2.1 Discrete-Time Signals
    2.2 Discrete-Time Systems
    2.3 Analysis of Discrete-Time Linear Time-Invariant systems
    2.4 Discrete-Time Systems Described by Difference Equations
    2.5 Implementation of Discrete-Time Systems
    2.6 Correlation of Discrete-Time Signals
    2.7 Summary and References
    3 The Z-Transform And Its Application To The Analysis Of Lti Systems
    3.1 The z-Transform
    3.2 Properties of the z-Transform
    3.3 Rational z-Transforms
    3.4 Inversion of the z-Transform
    3.5 Analysis of Linear Time Invariant Systems in the z-Domain
    3.6 The One-sided z-Transform
    3.7 Summary and References
    4 Frequency Analysis Of Signals And Systems
    4.1 Frequency Analysis of Continuous-Time Signals
    4.2 Frequency Analysis of Discrete-Time Signals
    4.3 Frequency-Domain and Time-Domain Signal Properties
    4.4 Properties of the Fourier Transform for Discrete-Time Signals
    4.5 Summary and References
    5 Frequency Domain Analysis Of Lti Systems
    5.1 Frequency-Domain Characteristics of Linear Time-Invariant Systems
    5.2 Frequency Response of LTI Systems
    5.3 Correlation Functions and Spectra at the Output of LTI Systems
    5.4 Linear Time-Invariant Systems as Frequency-Selective Filters
    5.5 Inverse Systems and Deconvolution
    5.6 Summary and References
    6 Sampling And Reconstruction Of Signals
    6.1 Ideal Sampling and Reconstruction of Continuous-Time Signals
    6.2 Discrete-Time Processing of Continuous-Time Signals
    6.3 Analog-to-Digital and Digital-to-Analog Converters
    6.4 Sampling and Reconstruction of Continuous-Time Bandpass Signals
    6.5 Sampling of Discrete-Time Signals
    6.6 Oversampling A/D and D/A Converters
    6.7 Summary and References
    7 The Discrete Fourier Transform: Its Properties And Applications
    7.1 Frequency Domain Sampling:The Discrete Fourier Transform
    7.2 Properties of the DFT
    7.3 Linear Filtering Methods Based on the DFT
    7.4 Frequency Analysis of Signals Using the DFT
    7.5 The Discrete Cosine Transform
    7.6 Summary and References
    8 Efficient Computaiton Of The Dft: Fast Fourier Transform Algorithms
    8.1 Efficient Computation of the DFT: FFT Algorithms
    8.2 Applications of FFT Algorithms
    8.3 A Linear Filtering Approach to Computation of the DFT
    8.4 Quantization Effects in the Computation of the DFT
    8.5 Summary and References
    9 Implementation Of Discrete-Time Systems
    9.1 Structures for the Realization of Discrete-Time Systems
    9.2 Structures for FIR Systems
    9.3 Structures for IIR Systems
    9.4 Representation of Numbers
    9.5 Quantization of Filter Coefficients
    9.6 Round-Off Effects in Digital Filters
    9.7 Summary and References
    10 Design Of Digital Filers
    10.1 General Considerations
    10.2 Design of FIR Filters
    10.3 Design of IIR Filters From Analog Filters
    10.4 Frequency Transformations
    10.5 Summary and References
    11 Multirate Digital Signal Processing
    11.1 Introduction
    11.2 Decimation by a Factor D
    11.3 Interpolation by a Factor I
    11.4 Sampling Rate Conversion by a Rational Factor I/D
    11.5 Implementation of Sampling Rate Conversion
    11.6 Multistage Implementation of Sampling Rate Conversion
    11.7 Sampling Rate Conversion of Bandpass Signals
    11.8 Sampling Rate conversion by an Arbitrary Factor
    11.9 Applications of Sampling Rate Conversion
    11.10 Digital Filter Banks
    11.11 Two-Channel Quadrature Mirror Filter Bank
    11.12 M-Channel QMF Bank
    11.13 Summary and References
    12 Linear Prediction And Optimum Linear Filters
    12.1 Random Signals, Correlation Functions and Power Spectra
    12.2 Innovations Representation of a Stationary Random Process
    12.3 Forward and Backward Linear Prediction
    12.4 Solution of the Normal Equations
    12.5 Properties of the Linear Prediction-Error Filters
    12.6 AR Lattice and ARMA Lattice-Ladder Filters
    12.7 Wiener Filters for Filtering and Prediction
    12.8 Summary and References
    13 Adaptive Filters
    13.1 Applications of Adaptive Filters
    13.2 Adaptive Direct-Form FIR Filters-The LMS Algorithm
    13.3 Adaptive Direct-Form FIR Filters-RLS Algorithms
    13.4 Adaptive Lattice-Ladder Filters
    13.5 Summary and References
    14 Power Spectrum Estimation
    14.1 Estimation of Spectra from Finite-Dura...
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