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The Internet users are familiar with the Peer-to-Peer (P2P) application, which brings a lot of convenience as well as problems, especially the pressure on the network generated by the growing traffic and the security issues. In recent years, the classification and identification of P2P traffic is a more popular research area, there have been many mature and effective identification technologies. On...
the prediction method of workload of oil production program is studied and the forecasting software of oil production program is compiled by using C/S mode and integrated application Odac, SQL, OLE and other technologies that provides users with simple, user-friendly work environment. The application of the software will enhance efficiency of oil production program for the preparation and reduce labor...
The accuracy of eye gaze estimation by image information is affected by several objective factors, including the image resolution, anatomical structure of eye, posture change, etc. Especially, the irregular movements of head and eye are the main problem and key technology being researched. We describe an effective way of estimating the eye gazing from the elliptical features of one iris under the...
The high precision of a piezo-electric positioning stage almost depends on whether the designed controller can effectively compensate the inherent hysteresis phenomenon. In this paper, an adaptive output feedback controller based on a radial basis function neural network (RBFNN) is proposed to eliminate the tracking errors caused by the hysteresis behavior. The observer-based RBFNN is used to online...
Classical linear dimensional reduction algorithms, such as Linear Discriminant Analysis (LDA) and Locality Preserving Projections (LPP) have been widely used in computer vision and pattern recognition. However, when dealing with the multidimensional dataset, they usually first transform the original data to vectors, and then analyze the data in such a high dimensional space. This process inevitably...
In this paper, a Spiking Neural Network (SNN) based controller is designed to fulfill the task of formation control of multiple mobile robots. The neural network contains three layers with different neuron model for different layer: the input layer encodes the inputs including sensor and task-related information by leaky integrate-and-fire (LIF) neurons, the hidden layer uses the approximate coincidence...
This paper addresses the questions of improving convergence performance for back propagation (BP) neural network. For traditional BP neural network algorithm, the learning rate selection is depended on experience and trial. In this paper, based on Taylor formula the function relationship between the total quadratic training error change and connection weights and biases changes is obtained, and combined...
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