Description

Book Synopsis
Digital signal processing is essential for improving the accuracy and reliability of a range of engineering systems, including communications, networking, and audio and video applications. Using a combination of programming and mathematical techniques, it clarifies, or standardizes the levels or states of a signal, in order to meet the demands of designing high performance digital hardware.

Written by authors with a wealth of practical experience working with digital signal processing, this text is an excellent step-by-step guide for practitioners and researchers needing to understand and quickly implement the technology. Split into six, self-contained chapters, Digital Signal Processing: A Practitioner's Approach covers:

  • basic principles of signal processing such as linearity, stability, convolution, time and frequency domains, and noise;
  • descriptions of digital filters and their realization, including fixed point implementation, pipelining, and field

    Table of Contents
    Foreword.

    Preface.

    Acknowledgements.

    1. Processing of Signals.

    1.1 Organisation of the Book.

    1.2 Classification of Signals.

    1.3 Transformations.

    1.4 Signal Characterisation.

    1.5 Converting Analogue Signals to Digital.

    1.6 Signal Seen by the Computing Engine.

    1.7 It Is Only Numbers.

    1.8 Summary.

    References.

    2. Revisiting the Basics.

    2.1 Linearity.

    2.2 Linear System Representation.

    2.3 Random Variables.

    2.4 Noise.

    2.5 Propagation of Noise in Linear Systems.

    2.6 Multivariate Functions.

    2.7 Number Systems.

    2.8 Summary.

    References.

    3. Digital Filters.

    3.1 How to Specify a Filter.

    3.2 Moving-Average Filters.

    3.3 Infinite Sequence Generation.

    3.4 Unity-Gain Narrowband Filter.

    3.5 All-Pass Filter.

    3.6 Notch Filter.

    3.7 Other Autoregressive Filters.

    3.8 Adaptive Filters.

    3.9 Demodulating via Adaptive Filters.

    3.10 Phase Shift via Adaptive Filter.

    3.11 Inverse Problems.

    3.12 Kalman Filter.

    3.13 Summary.

    References.

    4. Fourier Transform and Signal Spectrum.

    4.1 Heterodyne Spectrum Analyser.

    4.2 Discrete Fourier Transform.

    4.3 Decimating the Given Sequence.

    4.4 Fast Fourier Transform.

    4.5 Fourier Series Coefficients.

    4.6 Convolution by DFT.

    4.7 DFT in Real Time.

    4.8 Frequency Estimation via DFT.

    4.9 Parametric Spectrum in RF Systems.

    4.10 Summary.

    References.

    5. Realisation of Digital Filters.

    5.1 Evolution.

    5.2 Development Process.

    5.3 Analogue-to-Digital Converters.

    5.4 Second-Order BPF.

    5.5 Pipelining Filters.

    5.6 Real-Time Applications.

    5.7 Frequency Estimator on the DSP5630X.

    5.8 FPGA Implementation of a Kalman Filter.

    5.9 Summary.

    References.

    6. Case Studies.

    6.1 Difference Equation to Program.

    6.2 Estimating Direction of Arrival.

    6.3 Electronic Rotating Elements.

    6.4 Summary.

    References.

    Appendix: MATLAB and C Programs.

    A.1 Chapter 1 MATLAB Programs.

    A.2 Chapter 2 MATLAB Programs.

    A.3 Chapter 3 MATLAB Programs.

    A.4 Chapter 4 MATLAB Programs.

    A.5 Chapter 5 Programs.

    A.6 Chapter 6 MATLAB Programs.

    A.7 Library of Subroutines.

    A.8 Some Useful Programs.

    Index.

Digital Signal Processing

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    A Hardback by Kaluri V. Rangarao, Ranjan K. Mallik

      Trusted by thousands of customers. See 2,385+ Customer Reviews

      View other formats and editions of Digital Signal Processing by Kaluri V. Rangarao

      Publisher: John Wiley & Sons Inc
      Publication Date: 18/11/2005
      ISBN13: 9780470017692, 978-0470017692
      ISBN10: 0470017694

      Description

      Book Synopsis
      Digital signal processing is essential for improving the accuracy and reliability of a range of engineering systems, including communications, networking, and audio and video applications. Using a combination of programming and mathematical techniques, it clarifies, or standardizes the levels or states of a signal, in order to meet the demands of designing high performance digital hardware.

      Written by authors with a wealth of practical experience working with digital signal processing, this text is an excellent step-by-step guide for practitioners and researchers needing to understand and quickly implement the technology. Split into six, self-contained chapters, Digital Signal Processing: A Practitioner's Approach covers:

      • basic principles of signal processing such as linearity, stability, convolution, time and frequency domains, and noise;
      • descriptions of digital filters and their realization, including fixed point implementation, pipelining, and field

        Table of Contents
        Foreword.

        Preface.

        Acknowledgements.

        1. Processing of Signals.

        1.1 Organisation of the Book.

        1.2 Classification of Signals.

        1.3 Transformations.

        1.4 Signal Characterisation.

        1.5 Converting Analogue Signals to Digital.

        1.6 Signal Seen by the Computing Engine.

        1.7 It Is Only Numbers.

        1.8 Summary.

        References.

        2. Revisiting the Basics.

        2.1 Linearity.

        2.2 Linear System Representation.

        2.3 Random Variables.

        2.4 Noise.

        2.5 Propagation of Noise in Linear Systems.

        2.6 Multivariate Functions.

        2.7 Number Systems.

        2.8 Summary.

        References.

        3. Digital Filters.

        3.1 How to Specify a Filter.

        3.2 Moving-Average Filters.

        3.3 Infinite Sequence Generation.

        3.4 Unity-Gain Narrowband Filter.

        3.5 All-Pass Filter.

        3.6 Notch Filter.

        3.7 Other Autoregressive Filters.

        3.8 Adaptive Filters.

        3.9 Demodulating via Adaptive Filters.

        3.10 Phase Shift via Adaptive Filter.

        3.11 Inverse Problems.

        3.12 Kalman Filter.

        3.13 Summary.

        References.

        4. Fourier Transform and Signal Spectrum.

        4.1 Heterodyne Spectrum Analyser.

        4.2 Discrete Fourier Transform.

        4.3 Decimating the Given Sequence.

        4.4 Fast Fourier Transform.

        4.5 Fourier Series Coefficients.

        4.6 Convolution by DFT.

        4.7 DFT in Real Time.

        4.8 Frequency Estimation via DFT.

        4.9 Parametric Spectrum in RF Systems.

        4.10 Summary.

        References.

        5. Realisation of Digital Filters.

        5.1 Evolution.

        5.2 Development Process.

        5.3 Analogue-to-Digital Converters.

        5.4 Second-Order BPF.

        5.5 Pipelining Filters.

        5.6 Real-Time Applications.

        5.7 Frequency Estimator on the DSP5630X.

        5.8 FPGA Implementation of a Kalman Filter.

        5.9 Summary.

        References.

        6. Case Studies.

        6.1 Difference Equation to Program.

        6.2 Estimating Direction of Arrival.

        6.3 Electronic Rotating Elements.

        6.4 Summary.

        References.

        Appendix: MATLAB and C Programs.

        A.1 Chapter 1 MATLAB Programs.

        A.2 Chapter 2 MATLAB Programs.

        A.3 Chapter 3 MATLAB Programs.

        A.4 Chapter 4 MATLAB Programs.

        A.5 Chapter 5 Programs.

        A.6 Chapter 6 MATLAB Programs.

        A.7 Library of Subroutines.

        A.8 Some Useful Programs.

        Index.

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