Multiservice capacity and interference statistics of the uplink of high altitude platforms (HAPs) for asynchronous and synchronous WCDMA system

In this work, the capacity and the interference statistics of the uplink of high-altitude platforms (HAPs) for asynchronous and synchronous WCDMA system assuming finite transmission power and imperfect power control are studied. Propagation loss used to calculate the received signal power is due to the distance, shadowing, and wall insertion loss. The uplink capacity for 3- and 3.75-G services is given for different cell radius assuming outdoor and indoor voice users only, data users only and a combination of the two services. For 37 macrocells HAP, the total uplink capacity is 3,034 outdoor voice users or 444 outdoor data users. When one or more than one user is an indoor user, the uplink capacity is 2,923 voice users or 444 data users when the walls entry loss is 10 dB. It is shown that the effect of the adjacent channels interference is very small.

Regularized logistic regression and multi-objective variable selection for classifying MEG data

This paper addresses the question of maximizing classifier accuracy for classifying task-related mental activity from Magnetoencelophalography (MEG) data. We propose the use of different sources of information and introduce an automatic channel selection procedure. To determine an informative set of channels, our approach combines a variety of machine learning algorithms: feature subset selection methods, classifiers based on regularized logistic regression, information fusion, and multiobjective optimization based on probabilistic modeling of the search space. The experimental results show that our proposal is able to improve classification accuracy compared to approaches whose classifiers use only one type of MEG information or for which the set of channels is fixed a priori.