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The statistical information reconstruction of images will be difficult and inaccurate when no conditional data or only hard data are available. Accuracy of reconstructed images can be improved, using soft data during the process of reconstruction. Integrating soft data with hard data, a method based on multiple-point geostatistics is proposed to reconstruct statistical information of images. During...
An anomaly intrusion detection algorithm based on minimal diversity is proposed. It can deal with mixed attributes, so overcomes the deficiencies of most unsupervised learning methods. Based on the minimal diversity measurement, we use a small amount of marked data to guide clustering. When detecting new records, we calculate its diversity from the existing clusters to determine its category. This...
There are a large quantity of non-certain and non-structure contents in the Web text at the present time. It is difficult to cluster the text by some normal classification methods. An algorithm of Web text clustering analysis based on fuzzy set is proposed in this paper, and the algorithm has been described in detail by example. The technique can improve the algorithm complexity of time and space,...
In this paper, BP and RBF models for evaluating the running reliability of communication networks is presented on the basis of artificial neural network. The applicability of the two neural networks are investigated to the reliability of communication networks system. The study shows that the model established by BP network has a good general ability and a slow impending speed, on the other hand,...
A method to realize the P2P network traffic classification based on the SVM is proposed. This method uses the network traffic statistical characteristic and SVM method that based on the statistical theory to classifies the different P2P traffic application. Mainly research on four kind of network traffic classification, in document sharing BitTorrent, in media flows PPLive, in network telephone Skype,...
Some target tracking occasions often requires to tracking a kind of target, such as human face, automobile and so on. A specific target tracking algorithm based on support vector machine (SVM) and AdaBoost is proposed. Moreover, the characteristic data of SVM is a critical factor to success to detecting target. The method selects part of Harr wavelet characters by AdaBoost as input data of SVM training...
The classification for similar features classes is quite difficult task in many existing pattern-recognition systems. When the amount of samples is insufficient, neural networking training is hard. The dimension reduction, classification, clustering etc serial steps in recognition process takes such much time that the practical recognizing application is ease to meet the real time requirement. The...
Pixel point gradient features represent much of the intrinsic structures of an image and can be used to the description of machine vision object. By ICA technique, pixel gradient data can be projected from a high-dimensional space to a lower-dimensional space, which reduce the redundancy with no image segment based on threshold. A method of visual object matching based on gradient ICA feature is provided...
To discriminate the quality on traditional Chinese medicines Eucommia Bark real-time, according to the characters of Eucommia Bark finger printer, the basic concepts of rough set are introduced briefly. For rough sets can only deal with discrete data, the discretization of data is the key factor in the rough sets applied in quality assessment, we present a method of discretization based on cluster...
Taking the example of designing classifier in intrusion detection system, this paper studies on samples selection problem for classifier and proposes a method fitting for large data set. First, use cluster analysis and the information known of classification to select boundary samples of each class. Then cluster for each class of the remaining non-border samples and adopt the method based on sample...
In this thesis, the radar echo reflectivity of severe precipitation in the flood season of Changjiang-Huaihe area was identified by a Back-Propagation (BP) Model of Artificial Neural Network (ANN). The trained network was applied in a precipitation progress in the same area in 2001. The results illustrate that: the single hide-layer BP ANN can be used to identify the target radar echo at a high succeed...
Many practical problems are characterized as decision making with multiple, conflicting and noncommensurable nonlinear objectives and complex criteria. Especially in the practice of purchasing decision making, many quantitative and qualitative factors must be considered, as well as the vagueness and imprecision among them, which makes the decision process more complicated and unstructured. For identifying...
As virtual classrooms become more and more popular, companies are focusing on developing collaboration tools that help boost the effectiveness of online learning environments. These tools are referred to as synchronous collaboration tools. However, few virtual classrooms have multi-video function. This paper develops a multi-video based virtual classroom (MVVC) by Java media framework (JMF), a new...
In SC-FDE (single carrier with frequency domain equalization) systems, the factor which affects the performance of systems seriously is synchronization. Based on the studying of the algorithm of T.Schmidl & D.Cox and H.Minn, a novel timing synchronization method is proposed towards the SC-FDE systems in this paper. The method takes advantage of the correlation of the training symbol what can efficiently...
There is a lack of general mail filtering system, which is not only compatible with several content-based filtering methods but also can realize automatic learning function by mail client. In this connection, this paper proposes GALMFS (general automatic learning mail filtering system). GALMFS realizes general design of mail filtering system through separating content-based filtering methods from...
In the last decade, the use of artificial neural networks (ANN) has become widely accepted in medical applications for accuracy for predictive inference, with potential to support and flexible non-linear modelling of large data sets. Feedforward neural network (FNN) is a kind of artificial neural networks, which has a better structure and been widely used. But there are still many drawbacks if we...
Combining the failure practical example, neural network analysis is used for diagnosis. Using the neural network in MATLAB to simulate the circuit fault system, this is using two different kinds of training functions. For the better analysis of failure diagnosis problems, firstly, using MATLAB software to simulate failure problems such as the emergence of regular power, short circuit and broken circuit...
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