Optimizing Parameters of Information-Theoretic Correlation Measurement for Multi-Channel Time-Series Datasets in Gravitational Wave Detectors

Data analysis in modern science using extensive experimental and observational facilities, such as a gravitational wave detector, is essential in the search for novel scientific discoveries. Accordingly, various techniques and mathematical principles have been designed and developed to date. A recently proposed approximate correlation method based on the information theory is widely adopted in science and engineering. Although the maximal information coefficient (MIC) method remains in the phase of improving its algorithm, it is particularly beneficial in identifying the correlations of multiple noise sources in gravitational-wave detectors including non-linear effects. This study investigates various prospects for determining MIC parameters to improve the reliability of handling multi-channel time-series data, reduce high computing costs, and propose a novel method of determining optimized parameter sets for identifying noise correlations in gravitational wave data.Comment: 11 pages, 8 figure

Maine Perspective, v 12, i 15

The Maine Perspective, a publication for the University of Maine, was a campus newsletter produced by the Department of Public Affairs which eventually transformed into the Division of Marketing and Communication. Regular columns included the UM Calendar, Ongoing Events, People in Perspective, Look Who\u27s on Campus, In Focus, and Along the Mall. The weekly newsletter also included position openings on campus as well as classified ads. Included in this issue, First-year enrollment continues to rise; John Glenn next Cohen lecturer; Council of Retired Employees formed by President Hoff; University scientist joining Mt. Everest expedition; and Taking GIS to the classroom

Characterization of systems for software defined radio

Mestrado em Engenharia Electrónica e TelecomunicaçõesEsta dissertação insere-se na área de electrónica de rádio frequência, mais precisamente na caracterização de sistemas para rádios definidos por software (SDR). Um SDR é aquele que possui a flexibilidade para sintonizar, filtrar, ajustar a taxa de transmissão e controlar o tipo de modulação através de software. O aparecimento de novas tecnologias no mercado obriga à utilização de uma quantidade considerável de hardware nos dispositivos de transmissão/recepção, assim uma solução consiste no uso de arquitecturas de SDR onde a conversão do sinal analógico para digital é executada o mais próximo possível da antena e, sendo depois todo o processamento efectuado digitalmente. Assim, nesta tese, é apresentado um modelo comportamental para receptores de SDR, que leva em conta os elementos chave da distorção não linear. Além disso, são apresentadas algumas comparações entre simulações e medidas usando sinais multi-seno e WiMax usando um receptor ideal de SDR. Finalmente, é proposto um novo sistema de caracterização para dispositivos de SDR. ABSTRACT: This dissertation is related to the radio frequency area, more specifically to the characterization of systems for software-defined radio. A software-defined radio is one that has the flexibility to tune, filter, set the transmission rate and control the modulation type only by software. The emergence of new technologies in the market forces the use of a considerable quantity of hardware in the transceivers systems, so a viable solution for this is to use SDR solutions where the analogue to digital conversion is made closest possible of the antenna and then make all the processing digitally. So, in this dissertation, a behavioral model for SDR front end receiver evaluation, that captures the key elements of the nonlinear distortion, is proposed. Moreover, some comparisons between measured and simulated results under multisine and WiMax excitations are presented using the ideal SDR receiver. Finally, a new instrumentation system for characterization of SDR front ends is proposed