Part 1 Understanding DSP and its uses
1 DSP -- what is it?
1.1 Introduction
1.2 DSP -- what is it?
1.3 DSP -- a very short history lesson
1.4 DSP -- where and how is it used?
1.5 DSP -- what are the benefits of processing signals digitally?
1.6 DSP -- how quickly can I get up to speed?
1.7 DSP -- how can I gat Started?
1.8 DSP -- the future
1.9 QueStions
2 Designing with DSP -- what's required?
2.1 Ovefview of DSP application design
2.2 DSP softwre development
2.3 Deve1oping and debugging real-time softwre
2.4 Hardware development platforms
2.5 Algorithm visualization and development
2.6 Questions
2.7 References
3 DSP devices -- what's inside?
3.1 Signal processing algorithms and applications
3.2 DSP characteristics and features
3.3 General purpose DSP device or ASIC?
3.4 DSP performance benchmarks
3.5 DSP system architectures
3.6 Data representation
3.7 What's inside a DSP device? A detailed look at the core
3.8 DSP arithmetic - a hardware perspective
3.9 Questions
3.10 References
4 DSP systems -- interfacing with the outside world
4.1 DSP devices -- beyond the core
4.2 Hardware interfacing and I/O control
4.3 System management and control
4.4 AIl the anaIog bitS and pieces (i.e. ADC DAC anti-aIiasing oversampling, at
4.5 Gatting signals in
4.6 Gatting signals out
4.7 Geding signals in and out
4.8 Digital up- and down-conversion
4.9 Interfacing with the real world
4.10 Questions
4.11 References
Part 2 DSP algorithm ToolBox -- making it happen
5 Applications ToolBox I: General-purpose algorithms
5.1 Introduction
5.2 Logical operations
5.3 Arithmatic operations
5.4 Basic System building blocks
5.5 Linear scaling
5.6 Waveform generation
5.7 Quadrature signal processing
5.8 Waveform modulation
5.9 Waveform datection/demodulation
5.10 Requency translation
5.11 Signal averaging
5.12 Automatic cootrol Sysems
5.13 Questions
Applications ToolBox II: Digital filter design
6.1 Introduction
6.2 General filter design options
6.3 Digital filter methods
6.4 Digital filter design options
6.5 Digital filter structures and quantization effects
6.6 Digital filter algorithms
6.7 Filter design summary
6.8 Filter design packages
6.9 Specialist filter types
6.10 Questions
7 Applications ToolBox III: Spectral analysis
7.1 The properties of signals
7.2 The discrate Fourier transform
7.3 The Fast Fourier Transform
7.4 FFT implementation using DSP
7.5 Using the discrate Fourier transform to process continuous signals
7.6 Discrate time convolution and correlation
7.7 Spectral analysis
7.8 Related transforms
7.9 Questions
7.10 References
8 Applications Tool Box IV: Specialist applications
8.1 Dynamic range control - dynamics processors
8.2 Paramatric equalizers
8.3 Audio effeCts algorithms
8.4 Audio data compression
8.5 Questions
8.6 References
Part 3 Theory and practice
9 Theory behind the algorithms -- how do they work?
9.1 Introduction
9.2 Chapter overview
9.3 Classification of signals
9.4 The DSP model
9.5 Signal analysis tools
9.6 Windowing and sampling
9.7 Information recovery from sampled signals
9.8 Linear System behavior
9.9 Application of analysis to the DSP system mode1
9.10 Frequency transform theory
9.11 Digital filter introduction
9.12 Getting Started with simple filters
9.13 Higher-order filter design theory
9.14 Questions
9.15 References
10 Putting it all together -- case studies
10.1 IntroduCtion
10.2 High-speed Internat wreless modem
10.3 DSP based audio processor
Appendix 1 Useful trigonometric identities and series expansions
Appendix 2 Derivation of continuous signal correlation and spedral density
functions from samples
Appendix 3 CD contents
Index
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