Stability analysis of proportional delayed projection neural network for quadratic programming problem

At present,projection neural network(PNN)with bounded time delay has been widely used for solving convex quadratic programming problem(QPP).However,there is little research concerning PNN with unbounded time delay.In this paper,we propose the proportional delayed PNN to solve QPP with equality constraints.By utilizing homeo morphism mapping principle,we prove the proportional delayed PNN exists with unique equilibrium point which is the optimal solution of QPP.Simultaneously,delay-dependent criteria about global exponential stability(GES)and global polynomial stability(GPS)are also acquired by applying the method of variation of constants and inequality techniques.On the other hand,when proportional delay factor q is equal to 1,the proportional delayed PNN becomes the one without time delay which still can be utilized for solving QPP.But in most situations,q is not equal to 1,and time delay is unpredictable and may be unbounded in the actual neural network,which causes instability of system.Therefore,it is necessary to consider proportional delayed PNN.A numerical example demonstrates that,compared with the proportional delayed Lagrange neural network,the proportional delayed PNN is faster in terms of convergence rate.The possible reason is that appropriate parameters make the model converge to the equilibrium point along the direction of gradient descent.

CONVERGENCE ANALYSIS OF SPECTRAL METHODS FOR INTEGRO-DIFFERENTIAL EQUATIONS WITH VANISHING PROPORTIONAL DELAYS

We describe the application of the spectral method to delay integro-differential equations with proportional delays. It is shown that the resulting numerical solutions exhibit the spectral convergence order. Extensions to equations with more general （nonlinear） vanishing delays are also discussed.

Polynomial dissipativity of proportional delayed BAM neural networks

This paper pays close attention to the global polynomial dissipativity(GPD)for proportional delayed BAM neural networks(PDBAMNNs).The global exponential dissipativity(GED)and the global dissipativity(GD)are also talked about.Under the help of novel Lyapunov functionals and a generalized Halanay inequality,a set of dissipative criteria for such systems are led out,together with the global polynomial attracting set(GPAS)and the global attracting set(GAS).Further,the relationship among GPD,GED and GD is unveiled.Finally,a proposed theoretical condition is validated through a simulation experiment.

Collocation Methods for A Class of Volterra Integral Functional Equations with Multiple Proportional Delays

In this paper,we apply the collocation methods to a class of Volterra integral functional equations with multiple proportional delays(VIFEMPDs).We shall present the existence,uniqueness and regularity properties of analytic solutions for this type of equations,and then analyze the convergence orders of the collocation solutions and give corresponding error estimates.The numerical results verify our theoretical analysis.

Numerical Solution for Neutral Delay Differential Equation of Constant or Proportional Type using Hybrid Block Method

Neutral Delay Differential Equation(NDDE)is a differential problem that has regularly existed in numerous occurrences and has represented a significant role in dealing with real-life phenomena,especially on their application in biological and physiological processes.A fifth-order two-point hybrid implicit multistep block method(2PIH5)has been formulated in this research for the numerical solution of Neutral Delay Differential Equation(NDDE).A Taylor series interpolation polynomial has been implemented in the formulation of the proposed 2PIH5.The order,consistency,and zero-stability for 2PIH5 have been illustrated.The analyses of convergence and stability test have been performed and discussed.The initial value problems for the first-order NDDE with constant or proportional delay have been solved using the proposed block method.Some numerical results for the proposed method have been presented to prove the adaptability and applicability of the proposed method in solving NDDE.The proposed method is proved to be comparable with the other existing methods.It is assumed to be reliable and efficient for solving the first-order NDDE with constant or proportional delay.