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# SIGNALS AND SYSTEMS

# 1. INTRODUCTION

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*) = ( *I*_{r}(*x,y*), *I*_{g}(*x,y*), *I*_{b}(*x,y*) ),
where *I*_{r}(*x,y*) is the intensity of the red colour
at point (*x,y*), *I*_{g} of the green colour
and *I*_{b} 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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