TY - JOUR
AU - Чумаков, В. І.
AU - Харченко, О. І.
AU - Побережний, А. А.
PY - 2022/09/30
Y2 - 2024/06/17
TI - Using of the Noise as Signal Enhancement Factor in Nonlinear System
JF - Visnyk NTUU KPI Seriia - Radiotekhnika Radioaparatobuduvannia
JA - RADAP
VL -
IS - 89
SE -
DO -
UR - https://radap.kpi.ua/radiotechnique/article/view/1785
SP - 5-10
AB - <p>The stochastic resonance (SR) effect is considered, which makes it possible to stand out a weak signal from an additive mixture with noise. The strongest effect is shown to occur at certain well-defined, optimal noise intensity. The term SR was introduced during studies of the oscillator bistable model, which was proposed to analyze the glacial periods repeatability on Earth. The model described the particle motion in a symmetric one-dimensional bistable potential under the action of periodic force under strong friction conditions. In subsequent studies, the effect of stochastic resonance was found in many systems and not only physical. The known results of the approximate solution of the SR equation are considered. This equation is solved by two methods: the method of linear response and the theory of two states. In these studies, analytical expressions for the gain and signal-to-noise ratio are obtained using a number of approximations: restrictions on the signal amplitude when the response is linear, and restrictions on the frequency of the signal. In addition, when comparing the two methods considered, their use to calculate the noise variance at which the SR effect occurs, is shown to lead to different results. This necessitates further research to develop an analytical apparatus and verify its reliability by numerical calculations. The results of numerical simulation of the stochastic resonator response on the influence of an additive mixture harmonic signal and white Gaussian noise are presented. The enrichment of the output signal with harmonics and effective noise suppression are shown. The signal-to-noise ratio at the output numerical calculation results dependence on the input noise variance are presented. As it seen the dependence is complex, where you can select a local maximum at a point that does not correspond to the known values of the input noise variance at different approximate solutions of the equation SR. It is shown that the stochastic resonator acts as a low-pass filter, while providing a significant reduction in the output noise level.</p>
ER -