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After subjects take part in the Mongolian Standard Speech Test, they have some divergent opinions about their tested results. In order to eliminate these divergences of the test results, a new window is opened to employ a kind of software to assist the testing of the Mongolian Standard Speech based on the comparisons of language features. Specifically speaking, after the subject's speech data are...
The important meaning of the optical fiber fusion defect recognition was introduced based on wavelet packet technique. Detecting the optical fiber fusion point by using the UltraPAC system, aiming at the defect feature, the method of analyzing and extracting the defect eigenvalue by using wavelet packet analysis and pattern recognition by making use of the wavelet neural network is discussed. This...
In the last decade significant progress in computer vision based control of unmanned ground vehicles (UGV) has been achieved. However, until now textural information has been somewhat less effective than color or laser range information. In this paper we propose a computer vision based cross country segmentation system that is capable of distinguishing cross-country road, grass and trees during day-time...
Fault diagnosis of induction motor is gaining importance in industry because of the need to increase reliability and to decrease possible loss of production due to machine breakdown. Due to environmental stress and many others reasons different faults occur in induction motor. Many researchers proposed different techniques for fault detection and diagnosis. However, many techniques available presently...
An improved clustering method used for cascaded intrusion detection is proposed in this paper. It can detect different kinds of intrusions by arranging the processing framework in a cascaded way, based on which we can abstract corresponding features to achieve clustering. Computer simulations based on the 1999 KDD CUP dataset show the effectiveness of the proposed approach in detecting various intrusions...
The investigation of potential microarray markers, which in turn will speed up the molecular analysis and provide reliable results on the benefit of patient care is of significant importance. Feature selection techniques, which aim at minimizing the dimensionality of the microarray data by keeping the most significant genes according to their expression values is a necessary component towards this...
3D reconstruction based on high-level features, such as line and plane, is an important development trend in Digital Photogrammetry and Computer Vision. A novel method for extracting stratight line is presented, which can be illustrated as follows. Firstly, image is preprocessed by Wallis filtering that is used to enhance the image contrast and reduce the noise, so it is easy to extract more lines...
The paper proposes a method for the classification of EEG signal based on machine learning methods. We analyzed the data from an EEG experiment consisting of affective picture stimuli presentation, and tested automatic recognition of the individual emotional states from the EEG signal using Bayes classifier. The mean accuracy was about 75 percent, but we were not able to select universal features...
This paper introduces a novel algorithm for features selection based on a Support Vector Decision Function (SVDF) and Forward Selection (FS) approach with a fuzzy inferencing model. In the new algorithm, Fuzzy Enhancing Support Vector Decision Function (Fuzzy ESVDF), features are selected stepwise, one at a time, by using SVDF to evaluate the weight value of each specified candidate feature, then...
Signal feature detection is one of spectrum sensing methods in cognitive radios. It can detect primary user reliably in low SNR regime. In this paper, an asymptotical chi2 test is extended to spectrum sensing in cognitive radios, and a joint detection scheme based on multiple cyclic frequencies is proposed. Simulation results show the improved performance of the proposed scheme in the low SNR regime.
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