The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Brain Computer Interface one of hopeful interface technologies between humans and machines. Electroencephalogram-based Brain Computer Interfaces have become a hot spot in the research of neural engineering, rehabilitation, and brain science. The artifacts are disturbance that can occur during the signal acquisition and that can alter the analysis of the signals themselves. Detecting artifacts produced...
Distinction of the type of modulated signals is very important in cognitive radio system. In this paper, a novel approach to signal classification is proposed for cognitive radio. Combining the spectral cyclostationary features, embed SVM into the framework of HMM to construct a hybrid HMM/SVM classifier for signal recognition. The simulation results show that the high performance and robustness of...
As an effective tool in pattern recognition and machine learning, support vector machine (SVM) has been adopted abroad. In developing a successful SVM classifier, eliminating noise and extracting feature are very important. This paper proposes the application of kernel PCA to SVM for feature extraction. Then PSO Algorithm is adopted to optimization of these parameters in SVM. The novel time series...
This paper introduces an approach to obtain the feature vectors of surface electromyography (sEMG) signal based on Hilbert Huang transform (HHT). An adaptive segmentation method that could effectively select appropriate intrinsic mode function (IMF) is proposed. With the features gathered by using the energy of one channel signal, we also provide an optimized strategy based on experiments and experiences...
The support vector machine (SVM) is receiving considerable attention for its superior ability to solve nonlinear classification, function estimation and density estimation. Least squares support vector machines (LS-SVM) are re-formulations to the standard SVMs. Motivated by the theory of multi-scale representations of signals and wavelet transforms, this paper presents a way for building a wavelet-based...
In literature there is a huge body of references available which compare various classifiers in a particular application. However, the reliability of such a comparison is only valid if the model parameters, performance criteria and training environment are chosen in a fair framework, as successful application of a classifier is dependent on the those parameters. In this study we attempt to answer...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.