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The paper investigates consensus problems for multi-agent systems with nonlinear algorithms. Group consensus algorithms with actuator saturation for the first-order and second-order multi-agent systems are proposed. In addition, the adaptive consensus algorithm with nonlinear dynamic is also given. By applying the graph theory, Lyapunov function, and(More)
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is an evolving tool for determining breast diseases. Assisted with computer-aided methods (CAD), DCE-MRI demonstrates its efficiency on breast cancer diagnosis. A crucial step for automatic DCE-MRI analysis is to separate breast regions from the noise-corrupted background on DCE-MRI images. In(More)
In this paper, we are concerned with the Cauchy problem on the compressible isentropic two-fluids Euler-Maxwell equations in three dimensions. The global existence of solutions near constant steady states with the vanishing electromagnetic field is established, and also the time-decay rates of perturbed solutions in L q space for 2 ≤ q ≤ ∞ are obtained. The(More)
Physical properties of the chaotic system play important roles on studying the innate character and deciding the practical predictability of the dynamics. For a short piece of undersampled chaotic signals, it is very hard to abstract the physical properties of the signal source from the sequence. In this paper, we model this type of data with global S-NURBS(More)
Cloud computing is an effective approach for organizing computing resource which can improve service capability of WMNs remarkably. However, some drawbacks of wireless networks exist inherently make the cloud computing in WMNs insecure with various threats. In this paper, a novel hierarchical framework which is more compatible for cloud computing in WMNs is(More)
Physical properties are obviously essential to study a chaotic system that generates discrete-time signals, but recovering chaotic properties of a signal source from small data is a very troublesome work. Existing chaotic models are weak in dealing with such case in that most of them need big data to exploit those properties. In this paper, geometric theory(More)
Breast density is a widely adopted measure for early breast cancer diagnose. In this paper, an automated breast density estimation method was proposed. Mammograms were analyzed using wavelet transform to extract tissue-like contents. A tissue image was then divided into fixed size sub-regions. The sub-regions were classified as high and low density(More)