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Idiopathic generalized epilepsy (IGE) and symptomatic generalized epilepsy (SGE) are two kinds of generalized epilepsy. In this study, we discussed the methods of automatically segmentation of MR images for patients with these two kinds of epilepsy. K-Means clustering, expectation-maximization, and fuzzy c-means algorithms were employed to perform segmentation on brain images for patients with IGE...
In this paper, the fault classification problem for waste heat recovery system based on support vector machine (SVM) is investigated. Firstly, two-class SVM classification algorithm is reviewed. Then the model and six kinds of faults in waste heat recovery systems (WHRSs) are briefly described. In order to effectively isolate these faults in WHRSs, key features are extracted using principal component...
In wireless ad hoc and sensor networks, localization is a fundamental service to provide location information for those nodes without GPS units. In this paper, we use a simple yet effective proximity measure, called Regulated Neighborhood Distance (RND), to measure the closeness between two neighboring nodes based on their neighbors' numbers. Furthermore, we propose a RND-based localization algorithm,...
Brain-machine interfaces (BMIs) use neural activity related to motion parameters to enable brain directly control external devices. Some linear and nonlinear decoding techniques have been used successfully to infer arm trajectory from neural data. Unfortunately, these One stage decoding techniques can hardly get high accuracy and low computational demands at the same time. Here we introduce a Two...
Market clearing price (MCP) forecasting techniques is very important for the development of the electricity market. A three-layered neural network is used to predict electricity prices. MCP is seen as a multi-input single-output system and the historical electricity price and load data is utilized in an electricity market. The neural network is based on Minimum Entropy Error (MEE) cost function and...
Adaptive modulation technique has been widely used in wireless communication systems and channel prediction plays an important role in adaptive modulation technique. Minimax probability machine shows good performance in classification and prediction by controlling the generalization error boundary and trying to make it lowest. In this paper, we introduce a nonlinear prediction algorithm of fast fading...
This paper presents a cognitive-based emotion classifier of Chinese vocabulary, which inherits the advantages of traditional statistical linguistics model. The concept of cognitive prototype theory in cognitive linguistics was applied for the filter of text characteristics, while HowNet, which can provide the interface of the calculation of semantic similarity, and The Corpus Annotation of Harbin...
In order to reduce the relativity and improve the separability of prototype pattern vectors, a spectral-based synergetic network learning algorithm is proposed in this paper. The most attractive feature of the new method is that its complexity is linear with data dimension. To approximate the optimal cut and prevent instability due to information loss, all eigenvectors are used. The eigenvalues and...
In this paper, the authors apply the tree-cotree splitting (TCS) algorithm to the TDFEM to alleviate the constraint on the time-step size and to improve the convergence of iterative solutions at each time step. Compared with the conventional TDFEM, application of the TCS algorithm maintains the accuracy of the TDFEM solution but significantly reduces the number of iterations per time step for a preconditioned...
Feature selection is an important pre-processing step for solving classification problems. A good feature selection method may not only improve the performance of the final classifier, but also reduce the computational complexity of it. Traditionally, feature selection methods were developed to maximize the classification accuracy of a classifier. Recently, both theoretical and experimental studies...
The accuracy of network coordinate (NC) which is comprehensively applied is suffering seriously from triangle inequality violations (TIVs). A novel approach - embeddable overlay networks (EON) - has been proposed to address this problem. It runs NC on an overlay environment where round trip times (RTTs) are measured with respect to overlay forwarding that has eliminated all the TIVs. In this paper,...
This paper presents a fuzzy PI+D controller design for a direct drive motion control system actuated by permanent magnet linear synchronous motor (PMLSM). The employed Fuzzy PI+D is derived from the conventional continuous-time linear PI+D controller. The resulting controller is a discrete-time fuzzy version of the conventional PI+D controller. The proportional, integral and derivative gains are nonlinear...
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