Analog noise tuning in threshold sensing devices: a neuro-fuzzy approach

Abstract

Several classes of systems (biological, geophysical, electronic) show interesting features when a suitable level of noise is either forced into or naturally present in their working environment. For example, this phenomenon has been used to improve the performance of some sensing devices. The main problem in dealing with noise-added systems is the identification of the relationship between the optimal noise variance and the system parameters. In previous works the authors suggested both analytical and experimental solutions to the problem of optimal noise level tuning in stochastic systems. In particular, an experimental device giving the desired system performance has been tested. In this paper different working conditions are investigated and a new non-linear analogue realization of the tuning system is proposed.