Automatic Detection of the Common and Non-common Frequencies in Congruent Discrete Spectra. A Theoretical Approach
This work provides a theoretical foundation for automating spectral frequency detection, which could benefit scientists and engineers in routine signal processing tasks.
The paper presents a theoretical approach for automatically detecting common and non-common frequencies in congruent discrete spectra, addressing the need for automated spectral analysis without prior signal knowledge.
Both sampling a time-varying signal, and its spectral analysis are activities subjected to theoretically compelling, such as Shannon's theorem and the objectively limiting of the frequency's resolution. Usually, the signals' spectra are processed and interpreted by a scientist who, presumably, has sufficient prior information about the monitored signals to conclude on the significant frequencies, for example. On the other hand, processing and interpretation of signals' spectra can be routine tasks that must be automated using suitable software, i.e. PC application. In the above context, the paper presents the theoretic bases of an intuitive and practical approach of the (automatic) detection of the common and non-common frequencies in two or more congruent spectra.