scholarly journals Mean-Square Stability of Milstein Methods for Stochastic Pantograph Equations

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Feiyan Xiao ◽  
Tingting Qin ◽  
Chengjian Zhang
Keyword(s):  
Stability Criterion ◽  
Mean Square ◽  
Numerical Examples ◽  
Mean Square Stability ◽  
The Mean ◽  
Theoretical Results

This paper deals with nonlinear stochastic pantograph equations. For solving the equations, a class of extended Milstein methods are suggested. A mean-square stability criterion for this type of equations is presented. It is proved that under the suitable conditions the Milstein methods preserve the mean-square stability. Numerical examples further illustrate the obtained theoretical results.

scholarly journals Mean Square Stability of Impulsive Stochastic Differential Systems

2011 ◽  
Vol 2011 ◽  
pp. 1-13 ◽  
Author(s):  
Shujie Yang ◽  
Bao Shi ◽  
Mo Li
Keyword(s):  
Stochastic Analysis ◽  
Functional Method ◽  
Stochastic Equations ◽  
Mean Square ◽  
Differential Systems ◽  
Numerical Examples ◽  
Mean Square Stability ◽  
Analysis Theory ◽  
Delay Dependent ◽  
Theoretical Results

Based on Lyapunov-Krasovskii functional method and stochastic analysis theory, we obtain some new delay-dependent criteria ensuring mean square stability of a class of impulsive stochastic equations. Numerical examples are given to illustrate the effectiveness of the theoretical results.

Stability Criteria for Distributed Nonlinear Sampled-Data Systems Defined by Green’s Functions

1974 ◽  
Vol 96 (3) ◽  
pp. 315-321 ◽  
Author(s):  
G. Jumarie
Keyword(s):  
Stability Criterion ◽  
Feedback Gain ◽  
Continuous Systems ◽  
Mean Square ◽  
Data Systems ◽  
Sampled Data ◽  
Input Output ◽  
Output Stability ◽  
Lumped Parameter ◽  
The Mean

Sampled-data, nonlinear, distributed systems, which exhibit a structure similar to that of the standard closed loop with lumped parameter, are investigated from the viewpoint of their input-output stability. These systems are governed by operational equations involving discrete Laplace-Green kernels. Their feedback gains are bounded by upper and lower values which depend explicitly on the time and the distributed parameter. The main result is: an input-output stability theorem is given which applies both in L∞ (O, ∞) and L2 (O, ∞). This criterion, which may be considered as being an extension of the ≪circle criterion≫, involves the mean square value on the bounds of the feedback gain. Stability conditions for continuous systems are derived from this result. In the special case of systems with distributed periodical time-varying feedback gains, a stability criterion is given which applies in Marcinkiewicz space M2 (O, ∞). This result which involves the mean square value of the feedback gain is generally less restrictive than the L2 (O, ∞) stability criterion mentioned above.

scholarly journals Stochastic Memristive Quaternion-Valued Neural Networks with Time Delays: An Analysis on Mean Square Exponential Input-to-State Stability

Mathematics ◽  
2020 ◽  
Vol 8 (5) ◽  
pp. 815 ◽  
Author(s):  
Usa Humphries ◽  
Grienggrai Rajchakit ◽  
Pramet Kaewmesri ◽  
Pharunyou Chanthorn ◽  
Ramalingam Sriraman ◽  
...  
Keyword(s):  
Neural Networks ◽  
Continuous Time ◽  
Lyapunov Functional ◽  
Time Delays ◽  
System Model ◽  
Mean Square ◽  
New Class ◽  
Quaternion Multiplication ◽  
The Mean ◽  
Theoretical Results

In this paper, we study the mean-square exponential input-to-state stability (exp-ISS) problem for a new class of neural network (NN) models, i.e., continuous-time stochastic memristive quaternion-valued neural networks (SMQVNNs) with time delays. Firstly, in order to overcome the difficulties posed by non-commutative quaternion multiplication, we decompose the original SMQVNNs into four real-valued models. Secondly, by constructing suitable Lyapunov functional and applying It o ^ ’s formula, Dynkin’s formula as well as inequity techniques, we prove that the considered system model is mean-square exp-ISS. In comparison with the conventional research on stability, we derive a new mean-square exp-ISS criterion for SMQVNNs. The results obtained in this paper are the general case of previously known results in complex and real fields. Finally, a numerical example has been provided to show the effectiveness of the obtained theoretical results.

scholarly journals Statistical-mechanical analysis of adaptive filter with clipping saturation-type nonlinearity

2021 ◽  
Author(s):  
Seiji Miyoshi
Keyword(s):  
Steady State ◽  
Differential Equations ◽  
Asymptotic Analysis ◽  
Adaptive Filter ◽  
Adaptive System ◽  
Adaptive Signal Processing ◽  
Mean Square ◽  
Mean Square Stability ◽  
Statistical Mechanical ◽  
The Mean

Adaptive signal processing is used in broad areas. In most practical adaptive systems, there exists substantial nonlinearity that cannot be neglected. In this paper, we analyze the behaviors of an adaptive system in which the output of the adaptive filter has the clipping saturation-type nonlinearity by a statistical-mechanical method. To represent the macroscopic state of the system, we introduce two macroscopic variables. By considering the limit in which the number of taps of the unknown system and adaptive filter is large, we derive the simultaneous differential equations that describe the system behaviors in the deterministic and closed form. Although the derived simultaneous differential equations cannot be analytically solved, we discuss the dynamical behaviors and steady state of the adaptive system by asymptotic analysis, steady-state analysis, and numerical calculation. As a result, it becomes clear that the saturation value S has the critical value SC at which the mean-square stability of the adaptive system is lost. That is, when S > SC, both the mean-square error (MSE) and mean-square deviation (MSD) converge, i.e., the adaptive system is mean-square stable. On the other hand, when S < SC, the MSD diverges although the MSE converges, i.e., the adaptive system is not mean-square stable. In the latter case, the converged value of the MSE is a quadratic function of S and does not depend on the step size. Finally, SC is exactly derived by asymptotic analysis.<br>

scholarly journals A Comparison Theorem for Stability of Linear Stochastic Implicit Difference Equations of Index-1

2020 ◽  
Vol 36 (3) ◽  
Author(s):  
Nguyen Hong Son
Keyword(s):  
Comparison Theorem ◽  
Difference Equations ◽  
Mean Square ◽  
Mean Square Stability ◽  
Method Of Solution ◽  
The Mean ◽  
Definition Of

In this paper we study linear stochastic implicit difference equations (LSIDEs for short) of index-1. We give a definition of solution and introduce an index-1 concept for these equations. The mean square stability of LSIDEs is studied by using the method of solution evaluation. An example is given to illustrate the obtained results.

Cooperative guidance law considering the randomness of the unreliable communication network

2018 ◽  
Vol 233 (9) ◽  
pp. 3313-3322
Author(s):  
Chunyan Zhang ◽  
Jianmei Song ◽  
Lan Huang ◽  
Gaohua Cai
Keyword(s):  
Communication Network ◽  
Consensus Algorithm ◽  
Mean Square ◽  
Cooperative System ◽  
Proportional Navigation ◽  
Impact Time ◽  
Guidance Law ◽  
Mean Square Stability ◽  
Cooperative Guidance ◽  
The Mean

The cooperative attack problem of multiple missiles considering the randomness of the unreliable communication network is investigated. Firstly, the stochastic communication network is described by a Bernoulli random model. And the cooperative guidance law with unreliable communication network is proposed, which is composed of the upper consensus algorithm of desired impact time and the local proportional navigation with time-varying navigation gain. Each node of the upper cooperative system uses different update gain to adjust the desired impact time to improve the cooperative performance. Secondly, the mean square stability of the upper cooperative system is analyzed and proved. The explicit necessary and sufficient conditions of the mean square stability are presented for the two-missile cooperative attack system. And the analytic expression of the mean of the cooperative impact time is derived since it influences the attack precision directly and significantly. Thirdly, the effectiveness of the proposed cooperative guidance law with unreliable communication network is verified by simulation. And the influence of the update gain, the communication step, and the mean of link probability on the cooperative attack precision is analyzed.

scholarly journals Numerical Study on Stochastic Diabetes Mellitus Model with Additive Noise

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Zhifang Zhang ◽  
Qingyi Zhan ◽  
Xiangdong Xie
Keyword(s):  
Diabetes Mellitus ◽  
Existence And Uniqueness ◽  
Additive Noise ◽  
Numerical Solutions ◽  
Numerical Study ◽  
Stability And Convergence ◽  
Mean Square ◽  
Existence And Uniqueness Theorem ◽  
Mean Square Stability ◽  
The Mean

This article focuses on the numerical analysis and simulation of the stochastic diabetes mellitus model with additive noise. The existence and uniqueness theorem of the solution under some appropriate assumptions is established. And, the mean square stability and convergence of numerical solutions are proposed, too. The practical use of these theorems is demonstrated in the numerical computations of the stochastic diabetes mellitus model and the value for the forecast of the tendency of diabetes mellitus in a given time.

scholarly journals A Compensated Numerical Method for Solving Stochastic Differential Equations with Variable Delays and Random Jump Magnitudes

2015 ◽  
Vol 2015 ◽  
pp. 1-11
Author(s):  
Ying Du ◽  
Changlin Mei
Keyword(s):  
Differential Equations ◽  
Stochastic Differential Equations ◽  
Numerical Method ◽  
Analytical Solutions ◽  
Numerical Solutions ◽  
Mean Square ◽  
Variable Delays ◽  
Mean Square Stability ◽  
The Mean ◽  
Random Jump

Stochastic differential equations with jumps are of a wide application area especially in mathematical finance. In general, it is hard to obtain their analytical solutions and the construction of some numerical solutions with good performance is therefore an important task in practice. In this study, a compensated split-stepθmethod is proposed to numerically solve the stochastic differential equations with variable delays and random jump magnitudes. It is proved that the numerical solutions converge to the analytical solutions in mean-square with the approximate rate of 1/2. Furthermore, the mean-square stability of the exact solutions and the numerical solutions are investigated via a linear test equation and the results show that the proposed numerical method shares both the mean-square stability and the so-called A-stability.

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