What does the process of sampling do in signal processing?

The process of sampling in signal processing involves taking discrete measurements of an analog signal at specific intervals of time. This is essential for converting an analog signal, which is continuous by nature, into a digital form that can be processed, stored, and analyzed by digital systems. The sampling process captures the amplitude of the analog signal at these predefined intervals, allowing for the reconstruction of the signal in the digital domain.

In digital systems, these discrete samples can be manipulated and analyzed using various algorithms and software. The quality of this conversion is influenced by factors such as sampling rate and bit depth. A proper sampling rate ensures that sufficient information is captured to accurately represent the original signal without losing important characteristics, as governed by the Nyquist theorem.

The other processes mentioned do not pertain to the act of sampling itself. While increasing signal strength involves amplification, and reducing noise levels refers to filtering techniques, those processes are distinct from the function of sampling in the conversion of signals from analog to digital. Furthermore, converting a digital signal to analog is associated with a different process known as digital-to-analog conversion (DAC).