The design of two-dimensional signal constellations for the transmission of binary non-uniform memoryless sources over additive white Gaussian noise channels is investigated. The main application of this problem is the implementation of improved constellations where transmitted data is highly non-uniform. A simple algorithm, which optimizes a constellation by re-arranging its points in a pairwise fashion (i.e., two points are modified at a time, with all other points remaining fixed), is presented. In general, the optimized constellations depend on both the source statistics and the signal-to-noise ratio (SNR) in the channel. We show that constellations designed with source statistics considered can yield symbol error rate performance that is substantially better than rectangular quadrature amplitude modulation signal sets used with either Gray mapping or more recently developed maps. / Thesis (Master, Mathematics & Statistics) -- Queen's University, 2009-10-06 22:22:40.096

Linear programming (LP) decoding of low-density parity-check codes was introduced by Feldman et al. in [1]. In his formulation it is assumed that communication takes place over a memoryless channel and that the source is uniform. Here, we extend the LP decoding paradigm by studying its application to scenarios with source non-uniformity and to decoding over channels with memory. We develop two decoders for the scenario of non-uniform memoryless sources transmitted over memoryless channels. The first decoder uses a modified linear cost function which incorporates the a-priori source information and works with systematic codes. The second decoder differs by using non-systematic codes obtained by puncturing lower rate systematic codes and using an “extended decoding polytope.” Simulations show that the modified decoders yield gains over the standard LP decoder. Next, LP decoding is considered for two channels with memory: the binary additive Markov noise channel and the infinite-memory non-ergodic Polya-contagion channel. For the Markov channel, no linear cost function corresponding to maximum likelihood (ML) decoding could be obtained and hence it is unclear how to proceed. For the Polya channel, two LP-based decoders are developed. The first is derived in a straightforward manner from the ML decoding rule of [2]. The second decoder relies on a simplification of the same ML decoding rule which holds for codes containing the all-ones codeword. Simulations are performed for both decoders with regular and irregular LDPC codes and demonstrate relatively good performance with respect to the channel epsilon-capacity. / Thesis (Master, Mathematics & Statistics) -- Queen's University, 2008-12-08 16:24:43.358

Der Beitrag berichtet Ergebnisse und Erfahrungen eines E-Learning-Projekts zur Förderung von Kompetenzen zum Forschen und wissenschaftlichen Schreiben von Studierenden im Bereich der Sozial- und Wirtschaftswissenschaften. Das Projekt wurde gemeinsam von der Professur für Schlüsselqualifikationen der HTW Dresden und der Professur für Internationales Management und Unternehmensstrategie der TU Bergakademie Freiberg vom 01.07.2020 bis zum 31.12.2021 im Rahmen des Digital Fellowship-Programms durchgeführt und erfolgreich abgeschlossen. Da bestehende Formate wie die Präsenzlehre und digitale Angebote wie Foren hinsichtlich des komplexen Lernfelds die unterschiedlichen Lernstile und -strategien Studierender nur bedingt adressieren können, steht das studienbegleitende Konzept in Ergänzung zu bestehenden Angeboten wie wissenschaftlichen Seminaren und wird bei der Erstellung von Studienarbeiten genutzt. ... [Aus der Einleitung]