Estimation of exponential convergence rate and exponential stability for neural networks with time-varying delay

We study the problem of estimating the exponential convergence rate and exponential stability for neural networks with time-varying delay. Some criteria for exponential stability are derived by using the linear matrix inequality (LMI) approach. They are less conservative than the existing ones. Some analytical methods are employed to investigate the bounds on the interconnection matrix and activation functions so that the systems are exponentially stable.     

Exponential stability criterion for time-delay systems with nonlinear uncertainties

Exponential stability of time-delay systems with nonlinear uncertainties is studied in this paper. Based on the Lyapunov method and the approaches of decomposing the matrix, a new exponential stability criterion is derived in terms of a matrix inequality, which allows to compute simultaneously the two bounds that characterize the exponential nature of the solution. Some numerical examples are also given to show the superiority of our result to those in the literature.     

Exponential Stability for Delayed Stochastic Bidirectional Associative Memory Neural Networks with Markovian Jumping and Impulses

In this paper, the problem of stability analysis for a class of delayed stochastic bidirectional associative memory neural network with Markovian jumping parameters and impulses are being investigated. The jumping parameters assumed here are continuous-time, discrete-state homogeneous Markov chain and the delays are time-variant. Some novel criteria for exponential stability in the mean square are obtained by using a Lyapunov function, Ito’s formula and linear matrix inequality optimization approach. The derived conditions are presented in terms of linear matrix inequalities. The estimate of the exponential convergence rate is also given, which depends on the system parameters and impulsive disturbed intension. In addition, a numerical example is given to show that the obtained result significantly improve the allowable upper bounds of delays over some existing results.     

Exponential Stability for Delayed Stochastic Bidirectional Associative Memory Neural Networks with Markovian Jumping and Impulses

In this paper, the problem of stability analysis for a class of delayed stochastic bidirectional associative memory neural network with Markovian jumping parameters and impulses are being investigated. The jumping parameters assumed here are continuous-time, discrete-state homogenous Markov chain and the delays are time-variant. Some novel criteria for exponential stability in the mean square are obtained by using a Lyapunov function, Ito’s formula and linear matrix inequality optimization approach. The derived conditions are presented in terms of linear matrix inequalities. The estimate of the exponential convergence rate is also given, which depends on the system parameters and impulsive disturbed intension. In addition, a numerical example is given to show that the obtained result significantly improve the allowable upper bounds of delays over some existing results.     

New permanental bounds for Ferrers matrices

We survey the most recent results on permanental bounds of a nonnegative matrix. Some older bounds are revisited as well. Applying refinements of the arithmetic mean-geometric mean inequality leads to sharp bounds for the permanent of a fully indecomposable Ferrers matrix. In the end, several relevant examples comparing the bounds are discussed.     

Entrywise relative perturbation bounds for exponentials of essentially non-negative matrices

A real square matrix is said to be essentially non-negative if all of its off-diagonal entries are non-negative. We establish entrywise relative perturbation bounds for the exponential of an essentially non-negative matrix. Our bounds are sharp and contain a condition number that is intrinsic to the exponential function. As an application, we study sensitivity of continuous-time Markov chains. J. Xue was supported by the National Science Foundation of China under grant number 10571031, the Program for New Century Excellent Talents in Universities of China and Shanghai Pujiang Program. Q. Ye was supported in part by NSF under Grant DMS-0411502.     

Computational Krylov‐based methods for large‐scale differential Sylvester matrix problems

In the present paper, we propose Krylov‐based methods for solving large‐scale differential Sylvester matrix equations having a low‐rank constant term. We present two new approaches for solving such differential matrix equations. The first approach is based on the integral expression of the exact solution and a Krylov method for the computation of the exponential of a matrix times a block of vectors. In the second approach, we first project the initial problem onto a block (or extended block) Krylov subspace and get a low‐dimensional differential Sylvester matrix equation. The latter problem is then solved by some integration numerical methods such as the backward differentiation formula or Rosenbrock method, and the obtained solution is used to build the low‐rank approximate solution of the original problem. We give some new theoretical results such as a simple expression of the residual norm and upper bounds for the norm of the error. Some numerical experiments are given in order to compare the two approaches.     

Sharp bounds on the spectral radius of a nonnegative matrix

We give upper and lower bounds for the spectral radius of a nonnegative matrix using its row sums and characterize the equality cases if the matrix is irreducible. Then we apply these bounds to various matrices associated with a graph, including the adjacency matrix, the signless Laplacian matrix, the distance matrix, the distance signless Laplacian matrix, and the reciprocal distance matrix. Some known results in the literature are generalized and improved.     

Exponential estimates for singularly perturbed linear fuctional differential equations

Exponential estimates on the fundamental matrix, uniform on the perturbation parameter, are obtained for singularly perturbed systems of linear retarded functional differential equations, under the assumption that the eigenvalues of a certain coefficient matrix in the system have negative real parts. The exponential rates in the estimates are computable from upper bounds on the real parts of the characteristic values of the system or of associated simpler equations. Differences between differential-difference equations and equations with distributed delays are emphasized.     

Exponential convergence rate in entropy

The exponential convergence rate in entroy is studied for symmetric forms, with a special attention to the Markov chain with a state space having two points only. Some upper and lower bounds of the rate are obtained and five examples with precise or qualitatively exact estimates are presented.      

严格对角占优M-矩阵的逆矩阵的无穷大范数的新上界

给出了严格对角占优M-矩阵的逆矩阵的无穷大范数上界新的估计式,进而给出严格对角占优M-矩阵的最小特征值下界的估计式.新估计式改进了已有文献的结果.     

The deficit at ruin in the Sparre Andersen model with interest

In this paper, we consider the Sparre Andersen risk model modified by the inclusion of interest on the surplus. By using the techniques of Cai and Dickson [Ins.: Math. Econ. 32(2003)], we give the functional and also the exponential type upper bounds for the tail probability of the deficit at ruin. Some special cases are also discussed.     

广义特征值的扰动界限(Ⅰ)

到目前为止,关于广义特征值的扰动,已经建立了一些界限估计,但一般正则对的扰动界限难以算出.首先,定义某些基本参数,并利用这些参数建立几个关于一般正则矩阵对的广义特征值的扰动定理.这些定理给出的扰动界限的上界估计,一般是可以算出的.     

Exponential stabilization for a class of hybrid systems with mixed delays in state and control

This paper proposes a switching design for the exponential stabilization problem of hybrid systems with mixed time-delays in both the state and control. By using an improved Lyapunov–Krasovskii functional, a memoryless switching controller for the exponential stabilization of the system is designed in terms of linear matrix inequalities. The approach also allows us to compute simultaneously the two bounds that characterize the exponential stability rate of the solution.     

EXPONENTIAL ESTIMATES FOR STOCHASTIC DELAY HYBRID SYSTEMS WITH MARKOVIAN SWITCHING

This paper deals with the problem of norm bounds for the solutions of stochastic hybrid systems with Markovian switching and time delay.Based on Lyapunov-Krasovskii theory for functional differential equations and the linear matrix inequality(LMI)approach,mean square exponential estimates for the solutions of this class of linear stochastic hybrid systems are derived.Finally,An example is illustrated to show the applicability and effectiveness of our method.     

On the Complexity of Minimizing Quasicyclic Boolean Functions

We investigate the Boolean functions that combine various properties: the extremal values of complexity characteristics ofminimization, the inapplicability of local methods for reducing the complexity of the exhaustion, and the impossibility to efficiently use sufficient minimality conditions. Some quasicyclic functions are constructed that possess the properties of cyclic and zone functions, the dominance of vertex sets, and the validity of sufficient minimality conditions based on independent families of sets. For such functions, we obtain the exponential lower bounds for the extent and special sets and also a twice exponential lower bound for the number of shortest and minimal complexes of faces with distinct sets of proper vertices.     

Limitations of the hyperplane separation technique for bounding the extension complexity of polytopes

The hyperplane separation bound is a lower bound on the extension complexity of a polytope. It is the main tool in Rothvoß's proof of an exponential bound for the matching polytope (Rothvoß, 2017). We show that the technique is sensitive to the choice of slack matrix and does not improve upon the best known lower bounds for spanning tree and completion time polytopes when applied to their canonical slack matrices. Stronger bounds may be obtained by appropriate rescalings and redundancy.     

Reachable Set Bounding for Linear Discrete-Time Systems with Delays and Bounded Disturbances

This paper addresses the problem of reachable set bounding for linear discrete-time systems that are subject to state delay and bounded disturbances. Based on the Lyapunov method, a sufficient condition for the existence of ellipsoid-based bounds of reachable sets of a linear uncertain discrete system is derived in terms of matrix inequalities. Here, a new idea is to minimize the projection distances of the ellipsoids on each axis with different exponential convergence rates, instead of minimization of their radius with a single exponential rate. A smaller bound can thus be obtained from the intersection of these ellipsoids. A numerical example is given to illustrate the effectiveness of the proposed approach.     

非负矩阵Perron根的上下界

1.引言 本文主要讨论非负矩阵,我们将用B≥0和B>0分别表示矩阵B是非负的和正的,也就是B的每一个元素是非负的和B的每一个元素是正的.用p(B)表示方阵B的谱半径,当B≥0时,p(B)也就是B的perron根. 设(n)={1,2,…,n},A=(ai,j)是n×n非负矩阵,我们称     

Bounds on the inverses of nonnegative triangular matrices with monotonicity properties

Some bounds on the entries and on the norm of the inverse of triangular matrices with nonnegative and monotone entries are found. All the results are obtained by exploiting the properties of the fundamental matrix of the recurrence relation which generates the sequence of the entries of the inverse matrix. One of the results generalizes a theorem contained in a recent article of one of the authors about Toeplitz matrices.