Preface
Contents
Chapter 1: Introduction
1.1 Introduction
1.2 Installation and Setup
1.3 Numpy
1.3.1 Numpy Arrays and Memory
1.3.2 Numpy Matrices
1.3.3 Numpy Broadcasting
1.4 Matplotlib
1.5 Alternatives to Matplotlib
1.6 IPython
1.6.1 IPython Notebook
1.7 Scipy
1.8 Computer Algebra
1.9 Interfacing with Compiled Libraries
1.10 Other Resources
Appendix
Chapter 2: Sampling Theorem
2.1 Sampling Theorem
2.2 Reconstruction
2.3 The Story So Far
2.4 Approximately Time-Limited-Functions
2.5 Summary
Appendix
Chapter 3: Discrete-Time Fourier Transform
3.1 Fourier Transform Matrix
3.2 Computing the DFT
3.3 Understanding Zero-Padding
3.4 Summary
Appendix
Chapter 4: Introducing Spectral Analysis
4.1 Seeking Better Frequency Resolution with Longer DFT
4.2 The Uncertainty Principle Strikes Back!
4.3 Circular Convolution
4.4 Spectral Analysis Using Windows
4.5 Window Metrics
4.5.1 Processing Gain
4.5.2 Equivalent Noise Bandwidth
4.5.3 Peak Sidelobe Level
4.5.4 3-dB Bandwidth
4.5.5 Scalloping Loss
4.6 Summary
Appendix
Chapter 5: Finite Impulse Response Filters
5.1 FIR Filters as Moving Averages
5.2 Continuous-Frequency Filter Transfer Function
5.3 Z-Transform
5.4 Causality
5.5 Symmetry and Anti-symmetry
5.6 Extracting the Real Part of the Filter Transfer Function
5.7 The Story So Far
5.8 Filter Design Using the Window Method
5.8.1 Using Windows for FIR Filter Design
5.9 The Story So Far
5.10 Filter Design Using the Parks-McClellan Method
5.11 Summary
Appendix
References
Symbols
Index