Projeto e implementa����o de um pr��-regulador de fator de pot��ncia com controlo digital

Hoje em dia as fontes de alimenta����o possuem corre����o do fator de pot��ncia, devido ��s diversas normas regulamentares existentes, que introduziram grandes restri����es no que respeita �� distor����o harm��nica (THD) e fator de pot��ncia (FP). Este trabalho trata da an��lise, desenvolvimento e implementa����o de um Pr��-Regulador de fator de pot��ncia com controlo digital. O controlo digital de conversores com recurso a processamento digital de sinal tem vindo a ser ao longo dos ��ltimos anos, objeto de investiga����o e desenvolvimento, estando constantemente a surgirem modifica����es nas topologias existentes. Esta disserta����o tem como objetivo estudar e implementar um Pr��-Regulador Retificador Boost e o respetivo controlo digital. O controlo do conversor �� feito atrav��s da t��cnica dos valores m��dios instant��neos da corrente de entrada, desenvolvido atrav��s da linguagem de descri����o de hardware VHDL (VHSIC HDL ��� Very High Speed Integrated Circuit Hardware Description Language) e implementado num dispositivo FPGA (Field Programmable Gate Array) Spartan-3E. Neste trabalho s��o apresentadas an��lises matem��ticas, para a obten����o das fun����es de transfer��ncia pertinentes ao projeto dos controladores. Para efetuar este controlo �� necess��rio adquirir os sinais da corrente de entrada, tens��o de entrada e tens��o de sa��da. O sinal resultante do m��dulo de controlo �� um sinal de PWM com valor de fator de ciclo vari��vel ao longo do tempo. O projeto �� simulado e validado atrav��s da plataforma MatLab/Simulink e PSIM, onde s��o apresentados resultados para o regime permanente e para transit��rios da carga e da tens��o de alimenta����o. Finalmente, o Pr��-Regulador Retificador Boost controlado de forma digital �� implementado em laborat��rio. Os resultados experimentais s��o apresentados para validar a metodologia e o projeto desenvolvidos.

Uso de Interfaces C��rebro-computador na comunica����o de pessoas com S��ndrome de Encarceramento

Os avan��os nas Interfaces C��rebro-m��quina, resultantes dos avan��os no tratamento de sinal e da intelig��ncia artificial, est��o a permitir-nos aceder �� atividade cerebral, descodific��-la, e us��la para comandar dispositivos, sejam eles bra��os artificiais ou computadores. Isto �� muito mais importante quando os utilizadores s��o pessoas que perderam a capacidade de comunicar, embora mantenham as suas capacidades cognitivas intactas. O caso mais extremo desta situa����o �� o das pessoas afetadas pela S��ndrome de Encarceramento. Este trabalho pretende contribuir para a melhoria da qualidade de vida das pessoas afetadas por esta s��ndrome, disponibilizando-lhes um meio de comunica����o adaptado ��s suas limita����es. �� essencialmente um estudo de usabilidade aplicada a um tipo de utilizador extremamente diminu��do na sua capacidade de intera����o. Nesta investiga����o come��amos por compreender a S��ndrome de Encarceramento e as limita����es e capacidades das pessoas afetadas por ela. Abordamos a neuroplasticidade, o que ��, e em que medida �� importante para a utiliza����o das Interfaces C��rebro-m��quina. Analisamos o funcionamento destas interfaces, e os fundamentos cient��ficos que o suportam. Finalmente, com todo este conhecimento em m��os, investigamos e desenvolvemos m��todos que nos permitissem otimizar as limitadas capacidades do utilizador na sua intera����o com o sistema, minimizando o esfor��o e maximizando o desempenho. Foi para o efeito desenhado e implementado um prot��tipo que nos permitisse validar as solu����es encontradas.

Benchmarking de identifica����o de ano: cria����o de um site para benchmarking de t��cnicas de identifica����o de dano

Disserta����o para obten����o do grau de Mestre em Engenharia Mec��nica na ��rea de Manuten����o e Produ����o

Low-cost vibration sensors: tendencies and applications in condition monitoring of machines and structures

Trabalho Final de Mestrado para obten����o do grau de Mestre em Engenharia Mec��nica

Considerations about the choice of a differintegrator

Proceedings of the 2nd International Conference on Computational Cybernetics, Vienna University of Technology, August 30 - September 1, 2004

Retificador monof��sico com fator de pot��ncia quase unit��rio

Disserta����o para a obten����o do grau de Mestre em Engenharia Eletrot��cnica Ramo de Automa����o e Eletr��nica Industrial

ECG biometrics using a dissimilarity space representation

Electrocardiogram (ECG) biometrics are a relatively recent trend in biometric recognition, with at least 13 years of development in peer-reviewed literature. Most of the proposed biometric techniques perform classifi-cation on features extracted from either heartbeats or from ECG based transformed signals. The best representation is yet to be decided. This paper studies an alternative representation, a dissimilarity space, based on the pairwise dissimilarity between templates and subjects' signals. Additionally, this representation can make use of ECG signals sourced from multiple leads. Configurations of three leads will be tested and contrasted with single-lead experiments. Using the same k-NN classifier the results proved superior to those obtained through a similar algorithm which does not employ a dissimilarity representation. The best Authentication EER went as low as 1:53% for a database employing 503 subjects. However, the employment of extra leads did not prove itself advantageous.

Design and performance evaluation of turbo FDE receivers

Disserta����o apresentada na Faculdade de Ci��ncias e Tecnologia da Universidade Nova de Lisboa para obten����o do Grau de Mestre em Engenharia Electrot��cnica e de Computadores

Velocity estimation of moving ships using C-band SLC SAR data

A new algorithm for the velocity vector estimation of moving ships using Single Look Complex (SLC) SAR data in strip map acquisition mode is proposed. The algorithm exploits both amplitude and phase information of the Doppler decompressed data spectrum, with the aim to estimate both the azimuth antenna pattern and the backscattering coefficient as function of the look angle. The antenna pattern estimation provides information about the target velocity; the backscattering coefficient can be used for vessel classification. The range velocity is retrieved in the slow time frequency domain by estimating the antenna pattern effects induced by the target motion, while the azimuth velocity is calculated by the estimated range velocity and the ship orientation. Finally, the algorithm is tested on simulated SAR SLC data.

Parallel hyperspectral coded aperture for compressive sensing on GPUs

The application of compressive sensing (CS) to hyperspectral images is an active area of research over the past few years, both in terms of the hardware and the signal processing algorithms. However, CS algorithms can be computationally very expensive due to the extremely large volumes of data collected by imaging spectrometers, a fact that compromises their use in applications under real-time constraints. This paper proposes four efficient implementations of hyperspectral coded aperture (HYCA) for CS, two of them termed P-HYCA and P-HYCA-FAST and two additional implementations for its constrained version (CHYCA), termed P-CHYCA and P-CHYCA-FAST on commodity graphics processing units (GPUs). HYCA algorithm exploits the high correlation existing among the spectral bands of the hyperspectral data sets and the generally low number of endmembers needed to explain the data, which largely reduces the number of measurements necessary to correctly reconstruct the original data. The proposed P-HYCA and P-CHYCA implementations have been developed using the compute unified device architecture (CUDA) and the cuFFT library. Moreover, this library has been replaced by a fast iterative method in the P-HYCA-FAST and P-CHYCA-FAST implementations that leads to very significant speedup factors in order to achieve real-time requirements. The proposed algorithms are evaluated not only in terms of reconstruction error for different compressions ratios but also in terms of computational performance using two different GPU architectures by NVIDIA: 1) GeForce GTX 590; and 2) GeForce GTX TITAN. Experiments are conducted using both simulated and real data revealing considerable acceleration factors and obtaining good results in the task of compressing remotely sensed hyperspectral data sets.

Vertex component analysis GPU-based implementation for hyperspectral unmixing

Endmember extraction (EE) is a fundamental and crucial task in hyperspectral unmixing. Among other methods vertex component analysis ( VCA) has become a very popular and useful tool to unmix hyperspectral data. VCA is a geometrical based method that extracts endmember signatures from large hyperspectral datasets without the use of any a priori knowledge about the constituent spectra. Many Hyperspectral imagery applications require a response in real time or near-real time. Thus, to met this requirement this paper proposes a parallel implementation of VCA developed for graphics processing units. The impact on the complexity and on the accuracy of the proposed parallel implementation of VCA is examined using both simulated and real hyperspectral datasets.

Blind hyperspectral unmixing

Hyperspectral unmixing methods aim at the decomposition of a hyperspectral image into a collection endmember signatures, i.e., the radiance or reflectance of the materials present in the scene, and the correspondent abundance fractions at each pixel in the image. This paper introduces a new unmixing method termed dependent component analysis (DECA). This method is blind and fully automatic and it overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical based approaches. DECA is based on the linear mixture model, i.e., each pixel is a linear mixture of the endmembers signatures weighted by the correspondent abundance fractions. These abundances are modeled as mixtures of Dirichlet densities, thus enforcing the non-negativity and constant sum constraints, imposed by the acquisition process. The endmembers signatures are inferred by a generalized expectation-maximization (GEM) type algorithm. The paper illustrates the effectiveness of DECA on synthetic and real hyperspectral images.

Algorithms for time series clustering applied to biomedical signals

Thesis submitted in the fulfillment of the requirements for the Degree of Master in Biomedical Engineering

An��lise e implementa����o de filtros digitais fraccion��rios

O projeto realizado teve como tema a aplica����o das derivadas e integrais fraccion��rios para a implementa����o de filtros digitais numa perspetiva de processamento digital de sinais. Numa primeira fase do trabalho, �� efetuado uma abordagem te��rica sobre os filtros digitais e o c��lculo fraccion��rio. Estes conceitos te��ricos s��o utilizados posteriormente para o desenvolvimento do presente projeto. Numa segunda fase, �� desenvolvida uma interface gr��fica em ambiente MatLab, utilizando a ferramenta GUIDE. Esta interface gr��fica tem como objetivo a implementa����o de filtros digitais fraccion��rios. Na terceira fase deste projeto s��o implementados os filtros desenvolvidos experimentalmente atrav��s do ADSP-2181, onde ser�� poss��vel analisar e comparar os resultados experimentais com os resultados obtidos por simula����o no MatLab. Como quarta e ��ltima fase deste projeto �� efetuado uma reflex��o sobre todo o desenvolvimento da Tese e o que esta me proporcionou. Com este relat��rio pretendo apresentar todo o esfor��o aplicado na realiza����o deste trabalho, bem como alguns dos conhecimentos adquiridos ao longo do curso.

A Random Access Protocol incorporating Multi-Packet Reception, Retransmission Diversity and Successive Interference Cancellation

8th International Workshop on Multiple Access Communications (MACOM2015), Helsinki, Finland.