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.
Energy crisis, global warming and depletion of ozone layer are the major factors looming the world today. Adequate utilization of renewable energy sources like wind, solar, biomass etc. prove to be the only alternative. As a result, these industries are rapidly gaining significance. The wind power industry is very promising and it is necessary for the wind farm power prediction to be exact. Prediction...
In this paper, we present an efficient learning algorithm for a Fully Complex-valued Radial Basis Function (FC-RBF) Network using a self-regulatory system. One of the important issues in gradient descent learning algorithm for complex-valued network is the proper selection of training data sequence. In general, it is assumed that the training data is uniformly distributed in the input space with non-recurrent...
Beamforming is an array signal processing problem of forming a beam pattern of an array of sensors. In doing so, beams are directed to the desired direction (beam-pointing) and the nulls are directed to interference direction (null-steering). In this paper, the performance of beamforming using the fully complex-valued RBF network (FC-RBF) with the fully complex-valued activation function is compared...
In a fully complex-valued feed-forward network, the convergence of the complex-valued back-propagation learning algorithm depends on the choice of the activation function, minimization criterion, initial weights and the learning rate. The minimization criteria used in the existing learning algorithms do not approximate the phase well in complex-valued function approximation problems. This aspect is...
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.