Any physical quantity, which depends on time, space or any other variable, is a signal.

More definitions you will find from Federal Standard 1037C.

1.1. Classification of Signals

- real, one channel
- complex
- vector valued, multichannel
- one dimensional
- multidimensional

Example 1.1 The picture of a colour tv can be considered as a two dimensional three channel signal,

I(x,y) = ( Ir(x,y),  Ig(x,y),  Ib(x,y) ),

where Ir(x,y) is the intensity of the red colour at point (x,y), Ig of the green colour and Ib the intensity of the blue colour.

In this course we are mainly dealing with one dimensional and single channel deterministic signals and so called SISO systems (single input, single output) and Fourier analysis of them. Besides of the Fourier analysis, we also consider one of the latest tools of signal analysis, namely wavelets. Some of the most important areas of applications are e.g. speech processing and telecommunication (data transmission).

Multidimensional and multichannel signals and systems (MIMO or MISO systems, having applications e.g. in image processing) will be treated elsewhere.

Some further classes of signals:

- continuous time signal
- discrete time signal
- discrete signal
- digital signal (<= quantization !)
- analog signal
- deterministic signal
- random signal (noise, stochastic process)
- power signal
- energy signal

Related to these signals we have:

- digital system
- discrete system
- analog system
- deterministic system
- linear system
- nonlinear system

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