Digital Signal Processing. A Practitioner's Approach

  • ID: 2170315
  • Book
  • 210 Pages
  • John Wiley and Sons Ltd
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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 programmable gate array (FGPA) implementation;
  • Fourier transforms, especially discrete (DFT), and fast Fourier transforms (FFT);
  • case studies demonstrating difference equations, direction of arrival (DoA), and electronic rotating elements, and MATLAB programs to accompany each chapter.

A valuable reference for engineers developing digital signal processing applications, this book is also a useful resource for electrical and computer engineering graduates taking courses in signal processing.

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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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Kaluri V. Rangarao
Ranjan K. Mallik
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