VANHA VERSIO... 1 Introduction 1 1.1 Digital signal processing and its benefits 1.2 Application areas 1.3 Key DSP operations 1.4 Overview of real-time signal processing 1.5 Application examples 1.6 Summary. Problems. 2 Discrete transforms 47 2.1 Introduction 2.2 DFT and its inverse 2.3 Properties of the DFT 2.4 Computational complexity of the DFT 2.5 The decimation-in-time fast Fourier transform algorithm 2.6 Inverse fast Fourier transform 2.7 Implementation of the FFT 2.8 Other discrete transforms 2.9 Worked examples 3 The z-transform and its applications in signal processing 103 3.1 Discrete-time signals and systems 3.2 The z-transform 3.3 The inverse z-transform 3.4 Properties of the z-transform 3.5 Some applications of the z-transform in signal processing 3.6 Summary. Problems. 4 Correlation and convolution 183 4.1 Introduction 4.2 Correlation description 4.3 Convolution description 4.4 Implementation of correlation and convolution 4.5 Application examples 4.6 Summary. Problems. 5 A framework for digital filter design 251 5.1 Introduction to digital filters 5.2 Types of digital filters: FIR and IIR filters 5.3 Choosing between FIR and IIR filters 5.4 Filter design steps 5.5 Illustrative examples 5.6 Summary. Problems. 6 Finite impulse response (FIR) filter design 278 6.1 Introduction 6.2 FIR filter design 6.3 FIR filter specifications 6.4 FIR coefficient calculation methods 6.5 Window method 6.6 The optimal method 6.7 Frequency sampling method 6.8 Realization structures for FIR filters 6.9 Finite wordlength effects in FIR digital filters 6.10 FIR implementation techniques 6.11 Design example 6.12 Summary 6.13 Application examples of FIR filters 7 Design of infinite impluse response (IIR) digital filters 374 7.1 Introduction: summary of the basic features of IIR filters 7.2 Design stages for digital IIR filters 7.3 Stage 1: performance specification 7.4 Stage 2: calculation of IIR filter coefficients 7.5 Stage 3: realization structures for IIR digital filters 7.6 Stage 4: analysis of finite wordlength effects 7.7 Stage 5: implementation of the filter 7.8 A detailed design example of an IIR digital filter 7.9 Summary 7.10 Application examples 8 Multirate digital signal processing 491 8.1 Introduction 8.2 Concepts of multirate signal processing 8.3 Design of practical sampling rate converters 8.4 Software implementation of sampling rate converters- decimators 8.5 Software implementation of interpolators 8.6 Application examples 8.7 Summary 9 Adaptive digital filters 541 9.1 When to use adaptive filters and where they have been used 9.2 Concepts of adaptive filtering 9.3 Basic Wiener filter theory 9.4 The basic LMS adaptive algorithm 9.5 Recursive least squares algorithm 9.6 Application example 1 - adaptive filtering of ocular artefacts from the human EEG 9.7 Application example 2 - adaptive telephone echo cancellation 9.8 Other applications 10 Spectrum estimation and analysis 577 10.1 Introduction 10.2 Principles of spectrum estimation 10.3 Traditional methods 10.4 Modern parametric estimation methods 10.5 Comparison of estimation methods 10.6 Application examples 10.7 Summary 10.8 Worked example 11 General- and special-purpose hardware for DSP 614 11.1 Introduction 11.2 Computer architectures for signal processing 11.3 General-purpose digital signal processors 11.4 Implementation of DSP algorithms on general-purpose digital signal processors 11.5 Special-purpose DSP hardware 11.6 Summary 12 Applications and case studies 679 12.1 TMS320C10 target board for real-time DSP 12.2 TMS320C25 target board for real-time DSP 12.3 TMS320C25 Software Development System (SWDS) 12.4 FFT spectrum analyser 12.5 Detection of foetal heartbeats during labour 12.6 Real-time adaptive removal of ocular artefacts from human EEGs 12.7 Fixed- and floating point implementation of DSP systems 12.8 Equalization of digital audio signals 12.9 Adaptive ocular artefact filter 12.10 Summary

Jukka Parviainen Last modified: Thu Jul 11 15:19:53 EEST 2002