Chaptre 1

Signal processing involves a set of techniques for creating, analysing, and transforming signals with the goal of their optimal utilization. It draws from mathematics, physics (with a focus on wave physics), electronics, and computer science [1]. The primary objective is to extract the most useful information from a signal, especially when it is disturbed by noise.

Applications:

The field of signal processing finds application in various domains related to the transmission and processing of information. Its diverse sectors range from telecommunications (telephone, television, fax, modem, etc.) to instrumentation (sensors, metrology, spectral analysis, signal generation, etc.), automation (motor control, machinery, servos, robotics, etc.), biomedical engineering (radiography, ultrasound, etc.), sound processing (synthesisers, artificial echo, etc.), and image processing (image restoration, shape recognition, image compression and transmission, etc.). It also extends to geophysical signals, radar signals, sonar signals, and more.

Example :

Figure 3 illustrates the transmission chain, where noise introduces itself at various stages, including the coding level (transmitter), the transmission channel (radiation, coupling), and the receiver level. At the receiver stage, signal processing is applied to extract the noise signal, which represents uninteresting information.