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This paper considers the controller design problem for mean-square asymptotical synchronization of discrete-time neural networks with time-varying delay. By applying Lyapunov function method, a delay-dependent sufficient condition is proposed and formulated in the form of linear matrix inequalities(LMIs). Meanwhile, the feedback controller is derived to guarantee the asymptotical stability of the...
Finding the connected components of an undirected network is a fundamental computational problem at the heart of many network applications and has been applied in many fields, such as communication network robustness and computer vision. This paper presents a new form of graph contraction referred to as the “hub contraction,” in which the node with the maximum degree is selected as the central node,...
Convolutional Neural Network(CNN) is a kind of deep learning and it has become a current hot topic in the field of image recognition. In the CNN, Output layer consists of Euclidean Radial Basis Function, unit matrix column as CNN's label vector. The category of the input image can be interpreted as the nearest label vector. This paper addresses a question: what is CNN's optimal label vector? We show...
Using the cone theory, the existence and uniqueness of solutions for a class of systems of abstract binary operator equations in Banach space are discussed, and the error estimations for the convergent iterative sequence are given. The results presented here generalize and unify some known results.
The purpose of this study is to provide a direction on developing effective web site marketing strategy for China hotels by evaluating, analyzing and comparing the web sites between China hotels and U.S. hotels. In the article, the web site marketing attributes were identified and categorized into four groups “information”, “communication”, “distribution” and “transaction” based on the ICDT model...
Classification of the numerical data is a very important research topic in machine learning. But the incomplete data is very common in real world application. And the existence of incomplete data degrades the learning quality of classification models. But the existence of incomplete data always decrease the quality of classification models, To show the definition of missing data more intuitively,...
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