The Jupyter notebooks are accessible in various ways
- Online as static web pages
- Online for interactive usage with binder
- Local for interactive usage on the user's computer by cloning / downloading the repository from https://github.com/jimmyg1997/Python-Digital-Signal-Processing-Basics
- Other online services (e.g. Google Colaboratory, Microsoft Azure, ...) provide environments for interactive execution of Jupyter notebooks as well. Local execution on your computer requires a local Jupyter/IPython installation.
Digital Signal Processing is concerned with the representation of signals by a sequence of numbers or symbols and the processing of these signals. Digital signal processing is a branch of the science of the signal processing. The other branch of the signal processing is Analog Signal Processing.
DSP includes the areas of signal processing like: audio and speech signal processing, sonar and radar signal processing, sensor array processing, spectral estimation, statistical signal processing, digital image processing, signal processing for communications, control of systems, biomedical signal processing, seismic data processing, etc.
The present notebooks cover fundamental aspects of digital signal processing. A focus is laid on a mathematical treatise. The discussion of the mathematical background is important to understand the underlying principles in a more general manner.
The material covers the following topics
- Analogic signal analysis x(t), Sampling, Reconstruction, FT
- Discrete signal analysis x[n], Windowing, DTFT, Lobe interpretation
- LTI systems, Transfer Function H(z) estimation, Impulse response h[n], Step response, Difference equation, Zero-pole map, ROC
- Frequency Response Y(ejΩ)
- DTMF decoding, FIR filtering methods (butterworth)
| Abbreviation | Explanation |
|---|---|
| FT | Fourier Transform |
| DFT | Discrete Fourier Transform |
| DTFT | Discrete-Time Fourier Transform |
| LTI | Linear Time-Invariant System |
| ROC | Region of Convergence |
| DTMF | Dual Tone Multi Frequency |