What is the specification for the minimum sampling rate in relation to the highest frequency signal recorded?

The Nyquist theory is fundamental in signal processing and data acquisition, particularly regarding sampling rates. According to the Nyquist theory, in order to accurately capture and reconstruct a signal without distortion or loss of information, the sampling rate must be at least twice the highest frequency present in that signal. This concept is known as the Nyquist rate.

When a signal is sampled below this critical rate, it can lead to a phenomenon known as aliasing, where higher frequency components of the signal are incorrectly represented as lower frequencies. By adhering to the Nyquist theory, practitioners ensure that the digital representation of the analog signal remains true to its original form, thus maintaining the integrity and quality of the data being processed.

The other options, while relevant in their own contexts, do not directly relate to the specifications for minimum sampling rates in relation to frequency signals. Ohm’s theory deals primarily with electrical circuits, Coulomb's law pertains to electrostatic forces, and the Paley-Winer theorem involves functions in mathematical analysis, none of which address the requirements for sampling rates in signal processing.