Title Foundation of Digital Signal Processing Data Compression Discrete Fourier Transform Analog To Digital Converter Digital Signal Processing Fourier Series 2.8 MB 485
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Preface
1 Definitions and applications of digital signal processing
1.1 What is digital signal processing?
1.2 For whom this book is written and its content
1.3 What is DSP used for?
1.4 Application areas
1.5 A little history
2 A linear systems toolbox
2.1 Introduction
2.2 Linear systems
2.3 Complex numbers
2.4 Calculus
2.5 Introduction to differential equations
2.6 Calculus and digital signal processing
2.7 Operational amplifiers
2.8 Final remarks: using linear systems theory
3 An introduction to high-level computer programming using Delphi
3.1 Introduction
3.2 Why Delphi?
3.3 General program structure
3.4 A blank Delphi program
3.6 A program to demonstrate some key Delphi capabilities
3.7 Advanced features of Delphi: writing components, the media player, DLLS and Windows API
3.8 Final remarks: programming and DSP
4 Analysis of simple electrical systems using complex impedance, differential and difference equations
4.1 Introduction
4.2 Complex impedance analysis
4.3 Differential equations in the analysis of circuits
4.4 Difference equations in the simulation of circuits
4.5 Final remarks: complex impedance, differential and difference equations in DSP
5 Introduction to convolution and correlation
5.1 Introduction
5.2 Using impulse function to represent discrete signals
5.3 Description of convolution
5.4 Auto-correlation and cross-correlation
5.5 Final remarks: convolution and the Fourier domain
6 Fourier analysis
6.1 Introduction
6.2 The continuous trigonometric Fourier series for periodic signals
6.3 Data representation and graphing
6.4 The continuous trigonometric Fourier series for aperiodic signals
6.5 Observations on the continuous Fourier series
6.6 Exponential representation of the Fourier series
6.7 The continuous Fourier transform
6.8 Discrete Fourier analysis
6.9 Introduction to the fast Fourier transform
6.10 Final remarks: from theory to implementation
7 Discrete Fourier properties and processing
7.1 Introduction
7.2 Discrete frequencies and spectral leakage
7.3 Side lobes and the use of window functions
7.4 Representation of spectral data
7.5 Considerations of phase
7.6 Key properties of the discrete Fourier transform
7.7 Common signal operations processing using the discrete Fourier transform
7.8 Final remarks: other properties and processing techniques associated with the DFT
8 Introduction to Laplace space and the Laplace transform
8.1 Introduction
8.2 Conceptual framework of the Laplace transform
8.3 A more detailed look at Laplace space
8.4 Stability, passive and active systems and cascade design
8.5 Final remarks: Laplace in relation to DSP
9 An introduction to z-space, the z-transform and digital filter design
9.1 Introduction
9.2 The z-transform: definitions and properties
9.3 Digital filters, diagrams and the z-transfer function
9.4 IIR filter design using poleŒzero placement: the program ztransfer.exe
9.5 FIR and IIR filters: merits and disadvantages
9.6 Final remarks: the z-transform in relation to FIR and IIR filters
10 Signal sampling, analog to digital and digital to analog conversion
10.1 Introduction
10.2 The process of sampling
10.3 Signal digitisation
10.4 Principles of analog to digital conversion
10.5 Principles of digital to analog conversion
10.6 ADCs and DACs in system
10.7 Final remarks: dynamic range of ADCs and DACs
11 The design and implementation of finite impulse response filters
11.1 Introduction
11.2 The window method
11.3 Phase linearity
11.4 The frequency sampling method
11.5 Software for arbitrary FIR design: Signal Wizard
11.6 Inverse filtering and signal reconstruction
11.7 Final remarks: FIR design and implementation algorithms
12 The design and implementation of infinite impulse response filters
12.1 Introduction
12.2 The bilinear z-transform: definitions
12.3 The BZT and second order passive systems
12.4 Digital Butterworth and Chebyshev IIR filters
12.6 PoleŒzero placement revisited
12.7 FIR expression of IIR responses
12.8 Observations on IIR and FIR filters
12.9 Final remarks: the classes of digital filter
13.1 Introduction
13.2 Brief theory of adaptive FIR filters
13.3 The least mean square adaptive FIR algorithm
13.4 Use of the adaptive filter in system modelling
13.5 Delayed (single) input adaptive LMS filters for noise removal
13.6 The true (dual input) adaptive LMS filter
13.7 Observations on real-time applications of adaptive filters
13.8 Final remarks on adaptive filters
14 The design and programming of real-time DSP systems Part 1: The Motorola DSP56309 processor Œ architecture and language
14.1 Introduction
14.2 The Motorola DSP56309
14.3 DSP563xx assembly language programming
14.4 Final remarks: the DSP56309
15 The design and programming of real-time DSP systems Part 2: Hardware and alogrithms
15.1 Introduction
15.2 Reset and clock system
15.3 Communication system
15.4 External memory system
15.5 The audio codec system
15.6 Hints on circuit layout
15.7 Real-time DSP algorithms
15.8 Final remarks: real-time system design
16 Concluding remarks
Appendix: Summary of the theory and algorithmic development of the fast Fourier transform
A.1 Introduction
A.2 Important algebraic notations
A.3 The re-composition equations
A.4 The FFT butterfly
A.5 Re-ordering the input data
A.6 Butterfly computations
A.7 Loop calculations
A.8 Program development
Bibliography and references
Index
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