Introduction
Physical quantities such as electrical voltage, power, or pressure vary over time, making them carriers of information. We simply refer to them as signals. In general, any information can be considered a signal. Unwanted signals can sometimes disrupt these signals, altering the information. One of the main objectives of signal processing is to reduce this disruption, known as noise, in comparison to useful signals, thereby improving the signal-to-noise ratio (SNR).
There are three components to the signal study:
- Signal theory : This involves modeling or identifying the signal, involving a temporal or frequency analysis of the signals. This study requires a mathematical approach to explore properties such as useful duration, amplitude over time, or the spectrum revealing the frequency composition of the signal. Signal theory is therefore the study of mathematical tools to describe a signal. Its fundamental objective is the mathematical description of signals.
- Signal processing : Before transmitting a signal, it is necessary to modulate, encode, or change its frequency. Similarly, upon reception, it may be necessary to demodulate it. This is the focus of signal processing. This field also encompasses signal interpretation, including decoding, demodulation, filtering, etc. It involves performing operations on the signal.
- Transmission : This involves mathematical tools to describe the transmission of information from a transmitting system to a receiving system.
Signal processing finds applications in various fields, such as detection and localization systems, industrial systems (for example, level control), as well as speech, sound, and image processing.