Weak signal detection based on Mathieu-Duffing oscillator with time-delay feedback and multiplicative noise
QiuBao Wang,
YueJuan Yang and
Xing Zhang
Chaos, Solitons & Fractals, 2020, vol. 137, issue C
Abstract:
This paper presents analytical studies of the stochastic differential equation with Mathieu-Duffing oscillator under velocity feedback control with a time delay. We derive the analytic expressions of the stationary probability density function by the stochastic center manifold and stochastic averaging method to investigate the stochastic bifurcation. We first propose a three-step procedure for weak signals detecting: (1) Ascertain the existence and detect the frequency by the “transient vacancy”(TV) of chaotic motion. (2) Detect the phase based on Melnikov function. (3) After that the frequency and phase are known, we detect the amplitude by the transition between chaotic and large-scale periodic motion. In addition, the effects of the time-delayed feedback on the theoretical chaotic threshold are investigated under Gaussian white noise based on the Langevin and the Melnikov function. The time-delayed feedback τ can reduce the theoretical chaotic threshold, which is beneficial to detect the weak signal with the change of motion state. Subsequently, the “TV” method has obvious advantages of higher accuracy from the perspective of numerical simulation.
Keywords: SDDEs; Weak signals; multiplicative noise; melnikov function (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077920302320
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:137:y:2020:i:c:s0960077920302320
DOI: 10.1016/j.chaos.2020.109832
Access Statistics for this article
Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros
More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().