Dongqing Wu

Uniformly Stability of Impulsive BAM Neural Networks with Delays

This paper is concerned with the stability of the impulsive bidirectional associative memory (BAM) neural networks with time delays. By means of Lyapunov function and analysis technique, sufficient conditions are obtained for the existence and uniformly stability of a unique equilibrium solution without assuming the activation function to be bounded, monotonic or differentiable. This stability property is independent of the stability behavior of continuous-time BAM model since the impulses do contribution to systems uniformly stability

Exponential stability and periodicity of impulsive cellular neural networks with time delays

Abstract This paper is concerned with the stability and periodicity for a class of impulsive neural networks with delays. By means of the Fixed point theory, Lyapunov functional and analysis technique, some sufficient conditions of exponential stability and periodicity are obtained. We can see that impulses do contribution to the stability and periodicity. An example is given to demonstrate the effectiveness of the obtained results.

Globally Exponential Stability of a Class of Neural Networks with Variable Delays

In this paper we study the globally exponential stability of a class of neural networks with time-varying delays. Applying idea of vector Lyapunov function, Young inequality and Halanay differential inequality with delay, the sufficient conditions for the existence and globally exponential stability of the equilibrium point are obtained

Exponential Stability of Bidirectional Associative Memory Neural Networks with Delays and Impulsive

In this paper, a model of impulsive BAMs neural networks is first formulated. We investigate impulsive effects on the stability of BAMs neural networks with delays and obtain some sufficient conditions ensuring exponential stability of the impulsive delay system.The results extend and improve some recent works for impulsive neural networks as well as non-impulsive neural networks.

Discussing of factory pattern in embroidery CAD

In embroidery CAD, embroidery module is one of the parts which are badly affected by requirements changes. Factory pattern provides a suitable solution to decouple client from server. In traditional factory pattern, since it was restricted by language, coupling degree between factory and other modules remains high. To cope with the problem, the paper presents a new factory pattern under reflection mechanism. New pattern could completely decouple embroidery module from other modules. The idea also offers an instructive idea for other traditional design pattern to innovate with the help of reflection mechanism.

Exponential stability of a class of impulsive neural networks with variable delays

The main purpose of this paper is to study the globally exponential stability of the equilibrium point for a class of impulsive neural networks with time-varying delays. Without assuming global Lipschitz conditions on the activation functions, applying idea of vector Lyapunov function, combining Halanay differential inequality with delay, the sufficient conditions for globally exponential stability of neural networks are obtained.

A note of “global exponential stability of reaction-diffusion recurrent neural networks with time-varying delays”

Employing general Halanay inequalities, Dinipsilas derivative and functional analysis techniques, several global exponential stability criteria of the equilibrium point are established for a class of delayed reaction-diffusion recurrent neural networks. These criteria are only dependent on the parameters of the system. The results correct some errors of the earlier publication.

Globally exponential stability of a class of neural networks with impulses and variable delays

In this paper, a class of impulsive neural networks with time-varying delays is considered to study the globally exponential stability New sufficient conditions for globally exponential stability are obtained by using the vector Lyapunov function, Young inequality and Halanay differential inequality with delay.

An Algorithm for drawing tunnel based on ObjectARX

Tunnel lines creation is a prominent problem in military map drawing. This paper discusses an algorithm to solve it. Algorithm was implemented based on ObjectARX. Paper also presents its applicability and limitation. Combined characteristics of tunnel line with existing relative algorithms, a new algorithm is provided. Furthermore, it discusses time complexity of algorithm. Algorithm has been applied to plug-in toolkit in a military graphics system which has gotten reputation among end users.

Criteria for exponential stability of neural networks with distributed delays

In this paper, the global exponential stability is studied for a class of cellular neural networks with distributed delays. With assuming global Lipschitz conditions on the activation functions, based on the vector Lyapunov function, using the technique by virtue of Young inequality and Halanay differential inequality with delay, some sufficient conditions are obtained to ensure the uniqueness equilibrium point and globally exponential stability.