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.

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.

scholarly journals Stochastic Stability of a Fractional Viscoelastic Plate Driven by Non-Gaussian Colored Noise

2021 ◽  
Author(s):  
Dongliang Hu ◽  
Yong Huang
Keyword(s):  
Lyapunov Exponent ◽  
Stochastic Stability ◽  
Colored Noise ◽  
Viscoelastic Plate ◽  
Dynamic Equations ◽  
Stochastic Dynamic ◽  
Gaussian Colored Noise ◽  
Moment Lyapunov Exponent ◽  
The Moment ◽  
Non Gaussian

Abstract In this paper, the moment Lyapunov exponent and stochastic stability of a fractional viscoelastic plate driven by non-Gaussian colored noise is investigated. Firstly, the stochastic dynamic equations with two degrees of freedom are established by piston theory and Galerkin approximate method. The fractional Kelvin–Voigt constitutive relation is used to describe the material properties of the viscoelastic plate, which leads to that the fractional derivation term is introduced into the stochastic dynamic equations. And the noise is simplified into an Ornstein-Uhlenbeck process by utilizing the path-integral method. Then, via the singular perturbation method, the approximate expansions of the moment Lyapunov exponent are obtained, which agree well with the results obtained by the Monte Carlo simulations. Finally, the effects of the noise, viscoelastic parameters and system parameters on the stochastic dynamics of the viscoelastic plate are discussed.

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