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.
This paper proposes an efficient learning mechanism to build fuzzy rule-based systems through the construction of sparse least-squares support vector machines (LS-SVMs). In addition to the significantly reduced computational complexity in model training, the resultant LS-SVM-based fuzzy system is sparser while offers satisfactory generalization capability over unseen data. It is well known that the...
The Least Squares Support Vector Machine (LS-SVM) is a modified SVM with a ridge regression cost function and equality constraints. It has been successfully applied in many classification problems. But, the common issue for LS-SVM is that it lacks sparseness, which is a serious drawback in its applications. To tackle this problem, a fast approach is proposed in this paper for developing sparse LS-SVM...
In this paper, we construct a novel control using LS-SVM matrix operator to achieve the stablization of wheeled under-actuated manipulators. Further, the relative degree of the regulated output is assumed to be known enabling the system is feedback linearizable. By Lyapunov's direct method, it is shown that the tracking error can be controlled in a small neighborhood of zero. The methodology is applicable...
We propose a methodology for discriminating between various types of normal and diseased brain tissue in medical images that utilizes vector quantization (VQ), an image compression technique, to extract discriminative texture features. Rather than focusing on images of the entire brain, we direct our attention to extracting local descriptors for individual regions of interest (ROIs) as determined...
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.