Table of Contents
1.2 ANALOGUE SIGNAL PROCESSING
1.7 THE RUNNING AVERAGE FILTER
1.8 REPRESENTATION OF PROCESSING SYSTEMS
1.10 FEEDBACK (OR RECURSIVE) FILTERS
Chapter 2: Discrete signals and systems
2.3 THE REPRESENTATION OF DISCRETE SIGNALS
2.9 THE TRANSFER FUNCTION FOR A DISCRETE SYSTEM
2.11 MATLAB AND SIGNALS AND SYSTEMS
2.13 DIGITAL SIGNAL PROCESSORS AND THE z-DOMAIN
2.14 FIR FILTERS AND THE z-DOMAIN
2.15 IIR FILTERS AND THE z-DOMAIN
3.2 POLES, ZEROS AND THE s-PLANE
3.3 POLE–ZERO DIAGRAMS FOR CONTINUOUS SIGNALS
3.6 FROM THE s-PLANE TO THE z-PLANE
3.8 DISCRETE SIGNALS AND THE z-PLANE
3.12 THE RELATIONSHIP BETWEEN THE LAPLACE AND z-TRANSFORM
3.14 THE FREQUENCY RESPONSE OF CONTINUOUS SYSTEMS
3.16 THE FREQUENCY RESPONSE OF DISCRETE SYSTEMS
Chapter 4: The design of IIR filters
4.4 THE DIRECT DESIGN OF IIR FILTERS
4.7 THE DESIGN OF IIR FILTERS VIA ANALOGUE FILTERS
4.10 THE IMPULSE-INVARIANT METHOD
4.14 MATLAB AND s-TO-z TRANSFORMATIONS
4.16 FREQUENCY TRANSFORMATION IN THE s-DOMAIN
4.17 FREQUENCY TRANSFORMATION IN THE z-DOMAIN
4.20 PRACTICAL REALIZATION OF IIR FILTERS
Chapter 5: The design of FIR filters
5.3 PHASE-LINEARITY AND FIR FILTERS
5.5 THE FOURIER TRANSFORM AND THE INVERSE FOURIER TRANSFORM
5.6 THE DESIGN OF FIR FILTERS USING THE FOURIER TRANSFORM OR ‘WINDOWING’ METHOD
5.7 WINDOWING AND THE GIBBS PHENOMENON
5.8 HIGHPASS, BANDPASS AND BANDSTOP FILTERS
5.11 THE DISCRETE FOURIER TRANSFORM AND ITS INVERSE
5.12 THE DESIGN OF FIR FILTERS USING THE ‘FREQUENCY SAMPLING’ METHOD
5.15 THE FAST FOURIER TRANSFORM AND ITS INVERSE
Answers to self-assessment tests and problems
Appendix A: Some useful Laplace and z-transforms
Appendix B: Frequency transformations in the s- and z-domains