Articles — Presentation

This paper addresses both the efficiency and the portability of a computer program in charge of the baseband signal processing of a GNSS receiver. Efficiency, in this context, refers to optimizing the speed and memory requirements of the software receiver. Specifically, the interest is focused on how fast the software receiver can process the incoming stream of raw signal samples and, in particular, if signal processing up to the position fix can be executed in real-time (and how many channels the host computer executing the receiver application can sustain in parallel). This is achieved by applying the concept of parallelization at different abstraction levels. The paper describes strategies based on task, data and instruction-level parallelism, as well as actual implementations released under an open source license and the results obtained with different commercially available computing platforms. At the same time, the proposed solution also addresses portability, understood as the usability of the same software in different computing environments.

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A beamer presentation on patterns for SoS reconfiguration, in the context of a non-intrusive load monitoring framework for residential energy disaggregation in Smart Grid

Presentation with equations

Source code for LaTeX I, a course for LaTeX beginners, including slides, handouts, exercises and notes. LaTeX I is a workshop provided by Cardiff University's Doctoral Academy. The materials are a modified version of those produced by UK TUG volunteers for a course provided for beginning LaTeX users. The materials were adapted for LaTeX I by Clea F. Rees. Both the original work and modifications are licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License. The original project is available as a GitHub repository maintained by Joseph Wright from https://github.com/uktug/latex-beginners-course/.

With the massive popularity of Bayes' Theorem as well as the default use of Gaussian/Normal distributions for common data sets, we were keen to better understand firstly, if the assumption to use the Normal distrubition on differing data sets was a fit or not, and secondly, how to take the Normal distribution and Bayes' Theorem and apply it in use via repeatable code.

Estudo baseado na revista Ensinos do Reino da Editora Didaquê - Lição 2

Série de estudos baseados na revista Ensinos do Reino da Editora Didaquê

Série de Estudos nas Parábolas de Jesus Cristo