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.
K-Means algorithm is one of the most used clustering algorithm for Knowledge Discovery in Data Mining. Seed based K-Means is the integration of a small set of labeled data (called seeds) to the K-Means algorithm to improve its performances and overcome its sensitivity to initial centers. These centers are, most of the time, generated at random or they are assumed to be available for each cluster....
This study addresses the general problem of efficient resource management in wireless networks with arbitrary time-varying topologies. Communication channels are assumed to generally accommodate multiple simultaneous transmissions. In this context, we focus our attention on the problem of distributed transmission power allocation and medium access by links (transmitter-receiver pairs) that require...
A digraph is weight-balanced if, at each node, the sum of the weights of the incoming edges (in-degree) equals the sum of the weights of the outgoing edges (out-degree). Weight-balanced digraphs play an important role in a variety of cooperative control problems, including formation control, distributed averaging and optimization. We call a digraph weight-balanceable if it admits an edge weight assignment...
In this paper, we present a novel adaptive step-size and block-size frequency-domain block least mean square (ASB-FBLMS) algorithm. The convergence speed and the steady stage error are two conflicting factors in the traditional frequency-domain block least mean square (FBLMS) algorithm. While our algorithm optimally increase the convergence speed while maintaining or reducing the steady stage error...
In this paper we present the minimum exact word error (exactMWE) training criterion to optimise the parameters of large scale speech recognition systems. The exactMWE criterion is similar to the minimum word error (MWE) criterion, which minimises the expected word error, but uses the exact word error instead of an approximation based on time alignments as used in the MWE criterion. It is shown that...
In this paper we consider a projection method for convex feasibility problem that is known to converge only weakly. Exploiting a property concerning the intersection of a family of convex closed sets, we present a condition that makes them strongly convergent, without additional assumptions
Efficient and successful use of genetic algorithms (GAs) requires careful selection of several parameter values. One such critical parameter is the processing time (or, number of generations) that is sufficient to ensure suitable convergence. Todate there is only limited guidance on this subject, and in most cases detailed knowledge of the structure and properties of the problem is necessary for such...
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.