Fluctuation-enhanced sensing (FES) is a specific type of chemical or biological sensing where the stochastic component, noise, of the sensor signal is analyzed.[1] The stages following the sensor in a FES system typically contain filters and preamplifier(s) to extract and amplify the stochastic signal components, which are usually microscopic temporal fluctuations that are orders of magnitude weaker than the sensor signal. Then selected statistical properties of the amplified noise are analyzed, and a corresponding pattern is generated as the stochastic fingerprint of the sensed agent. Often the power density spectrum of the stochastic signal is used as output pattern however FES has been proven effective with more advanced methods, too, such as higher-order statistics.