Southeast University

About: Southeast University is a education organization based out in Nanjing, China. It is known for research contribution in the topics: Computer science & MIMO. The organization has 66363 authors who have published 79434 publications receiving 1170576 citations. The organization is also known as: SEU.

Stability and Synchronization of Discrete-Time Markovian Jumping Neural Networks With Mixed Mode-Dependent Time Delays

Abstract: In this paper, we introduce a new class of discrete-time neural networks (DNNs) with Markovian jumping parameters as well as mode-dependent mixed time delays (both discrete and distributed time delays). Specifically, the parameters of the DNNs are subject to the switching from one to another at different times according to a Markov chain, and the mixed time delays consist of both discrete and distributed delays that are dependent on the Markovian jumping mode. We first deal with the stability analysis problem of the addressed neural networks. A special inequality is developed to account for the mixed time delays in the discrete-time setting, and a novel Lyapunov-Krasovskii functional is put forward to reflect the mode-dependent time delays. Sufficient conditions are established in terms of linear matrix inequalities (LMIs) that guarantee the stochastic stability. We then turn to the synchronization problem among an array of identical coupled Markovian jumping neural networks with mixed mode-dependent time delays. By utilizing the Lyapunov stability theory and the Kronecker product, it is shown that the addressed synchronization problem is solvable if several LMIs are feasible. Hence, different from the commonly used matrix norm theories (such as the M-matrix method), a unified LMI approach is developed to solve the stability analysis and synchronization problems of the class of neural networks under investigation, where the LMIs can be easily solved by using the available Matlab LMI toolbox. Two numerical examples are presented to illustrate the usefulness and effectiveness of the main results obtained.

A brief survey of program slicing

Abstract: Program slicing is a technique to extract program parts with respect to some special computation. Since Weiser first proposed the notion of slicing in 1979, hundreds of papers have been presented in this area. Tens of variants of slicing have been studied, as well as algorithms to compute them. Different notions of slicing have different properties and different applications. These notions vary from Weiser's syntax-preserving static slicing to amorphous slicing which is not syntax-preserving, and the algorithms can be based on dataflow equations, information-flow relations or dependence graphs.Slicing was first-developed to facilitate debugging, but it is then found helpful in many aspects of the software development life cycle, including program debugging, software testing, software measurement, program comprehension, software maintenance, program parallelization and so on.Over the last two decades, several surveys on program slicing have been presented. However, most of them only reviewed parts of researches on program slicing or have now been out of date. People who are interested in program slicing need more information about the up to date researches. Our survey fills this gap. In this paper, we briefly review most of existing slicing techniques including static slicing, dynamic slicing and the latest slicing techniques. We also discuss the contribution of each work and compare the major difference between them. Researches on slicing are classified by the research hot spots such that people can be kept informed of the overall program slicing researches.

Distributed finite-time containment control for double-integrator multiagent systems.

Abstract: In this paper, the distributed finite-time containment control problem for double-integrator multiagent systems with multiple leaders and external disturbances is discussed. In the presence of multiple dynamic leaders, by utilizing the homogeneous control technique, a distributed finite-time observer is developed for the followers to estimate the weighted average of the leaders' velocities at first. Then, based on the estimates and the generalized adding a power integrator approach, distributed finite-time containment control algorithms are designed to guarantee that the states of the followers converge to the dynamic convex hull spanned by those of the leaders in finite time. Moreover, as a special case of multiple dynamic leaders with zero velocities, the proposed containment control algorithms also work for the case of multiple stationary leaders without using the distributed observer. Simulations demonstrate the effectiveness of the proposed control algorithms.