Response probability density functions of Duffing–Van der Pol vibro-impact system under correlated Gaussian white noise excitations

2013 ◽  
Vol 392 (6) ◽  
pp. 1269-1279 ◽  
Author(s):  
Chao Li ◽  
Wei Xu ◽  
Jinqian Feng ◽  
Liang Wang
Keyword(s):  
White Noise ◽  
Probability Density ◽  
Gaussian White Noise ◽  
Response Probability ◽  
Probability Density Functions ◽  
Density Functions ◽  
Van Der Pol ◽  
Impact System

scholarly journals The Stochastic Stability of Internal HIV Models with Gaussian White Noise and Gaussian Colored Noise

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Xiying Wang ◽  
Yuanxiao Li ◽  
Xiaomei Wang
Keyword(s):  
White Noise ◽  
Probability Density ◽  
Stochastic Stability ◽  
Colored Noise ◽  
Gaussian White Noise ◽  
Probability Density Functions ◽  
Stochastic Dynamic ◽  
Density Functions ◽  
Gaussian Colored Noise ◽  
The Stability

In this paper, the stochastic stability of internal HIV models driven by Gaussian white noise and Gaussian colored noise is analyzed. First, the stability of deterministic models is investigated. By analyzing the characteristic values of endemic equilibrium, we could obtain that internal HIV models reach a steady state under the influence of RTI and PI drugs. Then we discuss the stochastic stability of internal HIV models driven by Gaussian white noise and Gaussian colored noise, based on probability density functions. The functional methods are carried out to derive the approximate Fokker-Planck equation of stochastic internal HIV systems and further obtain the marginal probability density functions. Finally, numerical results show that the noise intensities have a great influence on uninfected cell, infected cell, and virus particles, for predicting the stability of stochastic dynamic systems subjected to Gaussian white noise and Gaussian colored noise.

Response Analysis of van der Pol Vibro-Impact System with Coulomb Friction Under Gaussian White Noise

2018 ◽  
Vol 28 (13) ◽  
pp. 1830043 ◽  
Author(s):  
Meng Su ◽  
Wei Xu ◽  
Guidong Yang
Keyword(s):  
White Noise ◽  
Coulomb Friction ◽  
Gaussian White Noise ◽  
Original System ◽  
Stochastic Averaging ◽  
Response Analysis ◽  
State Variables ◽  
Van Der Pol ◽  
Impact System ◽  
The Impact

In this paper, the stationary response of a van der Pol vibro-impact system with Coulomb friction excited by Gaussian white noise is studied. The Zhuravlev nonsmooth transformation of the state variables is utilized to transform the original system to a new system without the impact term. Then, the stochastic averaging method is applied to the equivalent system to obtain the stationary probability density functions (pdfs). The accuracy of the analytical results obtained from the proposed procedure is verified by those from the Monte Carlo simulation based on the original system. Effects of different damping coefficients, restitution coefficients, amplitudes of friction and noise intensities on the response are discussed. Additionally, stochastic P-bifurcations are explored.

scholarly journals Improving AoA Localization Accuracy in Wireless Acoustic Sensor Networks with Angular Probability Density Functions

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 900 ◽  
Author(s):  
Bart Thoen ◽  
Stijn Wielandt ◽  
Lieven De Strycker
Keyword(s):  
Sensor Networks ◽  
White Noise ◽  
Probability Density ◽  
Probability Density Functions ◽  
Density Functions ◽  
Acoustic Sensor ◽  
Angle Of Arrival ◽  
Matching Algorithm ◽  
Acoustic Sensor Networks ◽  
Mems Microphone

Advances in energy efficient electronic components create new opportunities for wireless acoustic sensor networks. Such sensors can be deployed to localize unwanted and unexpected sound events in surveillance applications, home assisted living, etc. This research focused on a wireless acoustic sensor network with low-profile low-power linear MEMS microphone arrays, enabling the retrieval of angular information of sound events. The angular information was wirelessly transmitted to a central server, which estimated the location of the sound event. Common angle-of-arrival localization approaches use triangulation, however this article presents a way of using angular probability density functions combined with a matching algorithm to localize sound events. First, two computationally efficient delay-based angle-of-arrival calculation methods were investigated. The matching algorithm is described and compared to a common triangulation approach. The two localization algorithms were experimentally evaluated in a 4.25 m by 9.20 m room, localizing white noise and vocal sounds. The results demonstrate the superior accuracy of the proposed matching algorithm over a common triangulation approach. When localizing a white noise source, an accuracy improvement of up to 114% was achieved.

Sign in / Sign up

Export Citation Format

Share Document