Continuous signal processing

The aim of this course is to study different classes of continuous signals.
The main analysis tools (energy, correlation, frequency) are presented in the context of deterministic signals and then extended to random signals. Treatments such as windowing and filtering are also covered. This is the first step in discovering signal processing (which is used in a wide range of applications: speech, biomedical, image, video, mobile communications, radar, etc.).

mathematical concepts

General information on signals and systems: random signal, deterministic signal / periodic signal / examples of fields of application (speech, biomedical, radar, sonar, GPS, mobile communication, etc.). introduction to linear systems linear phase filter.

Temporal characterization of deterministic signals: mean, energy, correlation function, covariance function.

Frequency characterization of signals and systems: Fourier series expansion, Fourier transform, Wiener Khintchine theorem, energy and power spectral density, etc.

Random signal characterization: mean, autocorrelation function, stationarity in the broad sense, ergodicity.

Processing examples

1 course and exercise book.