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.
Based on the concept of sparse Bayesian learning, an expectation and maximization algorithm is proposed for cooperative spectrum sensing and locationing of the primary transmitters in cognitive radio systems. Different from typical approaches, not only the signal strength, but also the number and the radio power profiles of the primary transmitters are estimated, which greatly facilitates resource...
A novel ensemble neural network structure is presented for automatic classification of power quality disturbances. Power quality (PQ) disturbances analysis is the focus of power quality control. The characteristics of PQ disturbances include short duration, variety of types and so on. Power quality disturbances classification is the foundation of power quality control automation. Different types of...
The traditional SPM approach based on bag-of-features (BoF) requires nonlinear classifiers to achieve good image classification performance. This paper presents a simple but effective coding scheme called Locality-constrained Linear Coding (LLC) in place of the VQ coding in traditional SPM. LLC utilizes the locality constraints to project each descriptor into its local-coordinate system, and the projected...
Subspace learning based face recognition methods have attracted considerable interests in recently years, including principal component analysis (PCA), linear discriminant analysis (LDA), locality preserving projection (LPP), neighborhood preserving embedding (NPE), marginal fisher analysis (MFA) and local discriminant embedding (LDE). These methods consider an n1timesn2 image as a vector in Rn1...
While PCA learns a subspace that captures the variations of the data, it assumes the collected data is well pre-processed (i.e., the pictures for faces are aligned by eye corners), this usually introduces a huge mount of manual labor for human. While people have been developing automatic eye alignment tools for such purpose, detecting eyes with robustness and accuracy is still an open problem for...
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.