Gallery — Recent

HoTT

This is an IEEE based template that can be used for presenting your work on the Open Science Data Cloud. Use it for the PIRE Workshop challenge and other submissions such as the Supercomputing 2014 conference.

Linux es un sistema operativo: un conjunto de programas que permiten interactuar con el ordenador y ejecutar otros programas. La parte ms importante de un sistema operativo es el ncleo. En un sistema GNU/Linux, Linux es el ncleo. El Shell es el programa-interface y es un script para la terminal que solo tenemos que agregar la extensión .sh que provee la comunicacin entre el usuario y el Sistema operativo, sus funciones son: Servir como traductor de comandos, recibe los comandos internos del mismo sistema operativo y Shell se encarga de su ejecucin, en cambio si hablamos de comandos realizados por el usuario entre la funcin del kernel, el los ejecuta y se encarga de procesar sus rdenes.

A ranking system for tech stocks and bank stocks of S&P 500 companies

Estilos para código fonte para Java e R language!

Eficiˆencia de sistema de telhado verde extensivo em precipita¸c˜oes extremas: an´alise quantitativa e efeitos na mitiga¸c˜ao de inunda¸c˜oes urbanas. Template downloaded from: http://www.latextemplates.com

Compressive Sensing is a Signal Processing technique, which gave a break through in 2004. The main idea of CS is, by exploiting the sparsity nature of the signal (in any domain), we can reconstruct the signal from very fewer samples than required by Shannon-Nyquist sampling theorem. Reconstructing a sparse signal from fewer samples is equivalent to solving a under-determined system with sparsity constraints. Least square solution to such a problem yield poor `results because sparse signals cannot be well approximated to a least norm solution. Instead we use l1 norm(convex) to solve this problem which is the best approximation to the exact solution given by l0 norm(non-convex). In this paper we plan to discuss three applications of CS in estimation theory. They are, CS based reliable Channel estimation assuming sparsity in the channel is known for TDS-OFDM systems[1]. Indoor location estimation from received signal strength (RSS) where CS is used to reconstruct the radio map from RSS measurements[2]. Identifying that subspace in which the signal of interest lies using ML estimation, assuming signal lies in a union of subspaces which is a standard sparsity assumption according to CS theory[3]. Index terms : Compressive Sensing, Indoor positioning, fingerprinting, radio map, Maximum likelihood estimation, union of linear subspaces, subspace recovery.

Modelo de Dissertação do MNPEF. Este modelo está adaptado para a UFSC, mas pode facilmente ser modificado para atender a outras universidades.

Figures TIKZ du cours "L'effet Doppler" disponible à l'adresse : http://femto-physique.fr/optique/doppler.php