AKA digital signal processing (DSP). A signal is an information-carrying changing attribute of an entity, but in the digital sense, 'signal' refers to either received or transmitted streams/blocks of data, commonly representing real-world quantities such as audio levels, luminosity, pressure etc over time or distance. 'Processing' is the act of altering, analyzing or characterizing the data to retrieve/modify information inherent in the signal in question.
A signal is an information-carrying changing attribute of an entity, but in the digital sense, 'signal' refers to either received or transmitted streams/blocks of data, commonly representing real-world quantities such as audio levels, luminosity, pressure etc over time or distance.
These real-world quantities usually comes as analogue signals that are being sampled and quantized into a digital format, i.e. a sequence or higher-dimensional array of discrete numbers.
'Processing' is the act of altering, analyzing or characterizing the data to retrieve/modify information inherent in the signal in question.
Notice that questions not related to the programming of signal processing implementations but the signal processing theory behind are off-topic for Stack Overflow and should be posted to the appropriate sister site, dsp.stackexchange.
Common topics include:
- digital filtering;
- audio processing;
- image processing;
- sampling;
- data compression;
- spectral analysis;
Analysis tools commonly in practice are the Discrete Fourier Transform (DFT), especially its fast implementations (FFT); and wavelet transforms.
Common softwares used in the field include matlab; octave; python, especially with numpy/scipy; c/c++/c#/objective-c; java; and various assembly languages.
