Signals such as audio, music, sonar, image and video convey information about physical quantities that vary over time and space. Signals can, for example, describe acoustic vibrations or radio waves, and thus play an important role throughout engineering. To help engineers to record, process, transmit and understand this information, computational and mathematical tools are used.
In this module, you will study different principles used to analyse signals and will learn how signals are affected by certain systems. To do this, you will learn about fundamental concepts such as frequency analysis, spectral analysis and digital systems theory.
In frequency analysis, a signal is decomposed into different frequencies. As many systems affect different frequencies independently, such a description allows us to study a system by analysing how it affects different frequencies. For example, a loudspeaker can be described as a system and an engineer might be interested in designing this system so that it does not unduly boost or attenuate different frequencies, which would colour the sound of the speaker.
Spectral analysis also reveals the frequency content in a signal, but also takes account of the fact that most signals show significant random variation. These techniques are used, for example, to study physical systems and can be used to compare and relate different signals, such as, for example, the electrical signal driving a speaker and the acoustic signal reaching you ears.
Nowadays, when we analyse or process signals, we tend to use digital computers. Analogue signals thus need to be converted first to a digital representation. To understand when this is possible and to appreciate the errors that can occur if the correct requirements are not met, a more detailed understanding of this conversion process is required. This also leads to the related problem of analysing digital systems, using tools similar to those used for analogue, continuous systems.