# Difference between revisions of "Signal Processing"

Jump to navigation
Jump to search

Kourouklides (talk | contribs) |
Kourouklides (talk | contribs) |
||

Line 92: | Line 92: | ||

* [http://python-for-signal-processing.blogspot.co.uk/ Python for Signal Processing] using [http://ipython.org/ IPython] | * [http://python-for-signal-processing.blogspot.co.uk/ Python for Signal Processing] using [http://ipython.org/ IPython] | ||

* [https://docs.scipy.org/doc/scipy/reference/tutorial/signal.html Signal Processing (SciPy.Signal)] - Python | * [https://docs.scipy.org/doc/scipy/reference/tutorial/signal.html Signal Processing (SciPy.Signal)] - Python | ||

+ | * [https://github.com/epfl-lts2/gspbox GSPBox] - MATLAB | ||

+ | * [https://github.com/epfl-lts2/pygsp PyGSP] - Python | ||

* [http://libit.sourceforge.net/ Information Theory and Signal Processing Library (libit)] - C | * [http://libit.sourceforge.net/ Information Theory and Signal Processing Library (libit)] - C | ||

## Revision as of 19:43, 7 August 2018

This page contains resources about Signal Processing in general.

More specific information is included in each subfield.

## Contents

## Subfields and Concepts

*See Category:Signal Processing for some of its subfields.*

- Signal = Information and (additive/multiplicative) noise
- Noise
- Additive vs Multiplicative noise
- White, Pink, Red/Brownian, Grey noise
- Gaussian vs Non-Gaussian noise
- Additive White Gaussian noise (AWGN)

- Energy (in Signal Processing)
- Energy (in Physics) and Characteristic Impedance
- Energy-Based Model (EBM)

- Statistical Signal Processing / Adaptive Signal Processing
- Bayesian Signal Processing

- Digital Signal Processing
- Digital Image Processing
- State Space Analysis
- Linear Systems
- Discrete-time Systems
- Continuous-time Systems
- Linear Time-Invariant (LTI) Systems
- Time-Variant Systems

- Sampling (in Signal Processing)
- Sampling Theorem (by Whittaker–Nyquist–Kotelnikov–Shannon)
- Nyquist rate
- Signal Reconstruction
- Analog-to-Digital Conversion
- Digital-to-Analog Conversion
- Sparse Sampling / Compressed Sensing
- Adaptive Sampling / Active Learning
- Aliasing

- Transformations
- Fourier Transform
- Laplace Transform
- Z-Transform

- Harmonic Analysis
- Topological groups
- Pontryagin duality

- Filter Theory / Filter Analysis / Filter Design
- Low-pass filter (LPF) Vs High-pass filter (HPF)
- Linear filter Vs Nonlinear filter
- Finite Impulse Response (FIR) filter Vs Infinite Impulse Response (IIR) filter
- Time-invariant filer Vs Time-variant filter
- Causal filter Vs Non-causal filter
- Analog filter Vs Digital filter
- Discrete-time (sampled) filter or Continuous-time filter
- Gabor filter (in Digital Image Processing)

- Applications
- Electric Circuit Analysis
- Communication Systems
- Feedback Systems / Control Systems

## Online Courses

### Video Lectures

- Signals and Systems by Alan V. Oppenheim
- Signals and Systems by Dennis Freeman
- Signal and Systems by K S Venkatesh
- Signals and Systems by Suhash Chandra Dutta Roy
- ECE 2610: Introduction to Signals and Systems by Mark Wickert

### Lecture Notes

- EE102: Introduction to Signals & Systems by Stephen Boyd
- Signals and Systems - NPTEL
- ELEC 301 - Introduction to Signals and Systems by Richard Baraniuk
- Signals and Systems by Tania Stathaki
- Signals and Linear Systems by Peter Y. K. Cheung
- Signals and Systems by Rafaello D'Andrea
- Introduction to Communication, Control, and Signal Processing by Alan V. Oppenheim and George Verghese

## Books

- Oppenheim, A. V., & Verghese, G. C. (2015).
*Signals, systems and inference*. Pearson. - Haykin, S. S. (2013).
*Digital communications*. John Wiley & Sons. - Proakis, J. G., & Salehi, M. (2013).
*Fundamentals of communication systems*. Pearson. - Couch, L. W., Kulkarni, M., & Acharya, U. S. (2012).
*Digital and analog communication systems*. 8th Ed. Prentice Hall. - Haykin, S. & Moher M. (2009).
*Communication systems*. 5th Ed. International Student Version. John Wiley & Sons. - Lathi, B. P. (2011).
*Modern digital and analog communication systems*. 4th Ed. Oxford University Press. - Haykin, S. S., Moher, M., & Song, T. (2007).
*An introduction to analog and digital communications*. 2nd Ed. John Wiley & Sons. - Lathi, B. P. (2004).
*Linear Systems and Signals*. 2nd Ed. Oxford University Press. - Haykin, S., & Van Veen, B. (2002).
*Signals and systems*. 2nd Ed. John Wiley & Sons. - Proakis, J. G., Salehi, M., Zhou, N., & Li, X. (2001).
*Communication systems engineering*. 2nd Ed. Prentice Hall. - Lathi, B. P. (2000).
*Signal Processing and Linear Systems*. Oxford University Press. - Oppenheim, A. V., & Willsky, A. S. (1997).
*Signals and Systems*. Prentice Hall.

## Software

- Signal Processing Toolbox - MATLAB
- Python for Signal Processing using IPython
- Signal Processing (SciPy.Signal) - Python
- GSPBox - MATLAB
- PyGSP - Python
- Information Theory and Signal Processing Library (libit) - C

## See also

## Other Resources

- Signal Processing - Google Scholar Metrics (Top Publications)
- Signal Processing - Nature
- Signal Analysis/Processing Software - a list of software packages
- MATLAB Vs Python for Signal Processing - a discussion why MATLAB is essential for this field
- Signals and Systems by Wikibooks
- Signal Processing by Wikibooks