## Adaptive Stochastic Resonance (1998)

Venue: | Proceedings of the IEEE: special issue on intelligent signal processing |

Citations: | 17 - 9 self |

### BibTeX

@INPROCEEDINGS{Mitaim98adaptivestochastic,

author = {Sanya Mitaim and Bart Kosko},

title = {Adaptive Stochastic Resonance},

booktitle = {Proceedings of the IEEE: special issue on intelligent signal processing},

year = {1998},

pages = {2152--2183}

}

### Years of Citing Articles

### OpenURL

### Abstract

This paper shows how adaptive systems can learn to add an optimal amount of noise to some nonlinear feedback systems. Noise can improve the signal-to-noise ratio of many nonlinear dynamical systems. This "stochastic resonance" effect occurs in a wide range of physical and biological systems. The SR effect may also occur in engineering systems in signal processing, communications, and control. The noise energy can enhance the faint periodic signals or faint broadband signals that force the dynamical systems. Most SR studies assume full knowledge of a system's dynamics and its noise and signal structure. Fuzzy and other adaptive systems can learn to induce SR based only on samples from the process. These samples can tune a fuzzy system's if-then rules so that the fuzzy system approximates the dynamical system and its noise response. The paper derives the SR optimality conditions that any stochastic learning system should try to achieve. The adaptive system learns the SR effect as the sys...