868 resultados para FPGA parallel SAT solver


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Pós-graduação em Ciência da Computação - IBILCE

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Pós-graduação em Engenharia Mecânica - FEG

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O presente trabalho trata da filtragem e reconstrução de sinais em frequência intermediária usando FPGA. É feito o desenvolvimento de algoritmos usando processamento digital de sinais e também a implementação dos mesmos, constando desde o projeto da placa de circuito impresso, montagem e teste. O texto apresenta um breve estudo de amostragem e reconstrução de sinais em geral. Especial atenção é dada à amostragem de sinais banda-passante e à análise de questões práticas de reconstrução de sinais em frequência intermediária. Dois sistemas de reconstrução de sinais baseados em processamento digital de sinais, mais especificamente reamostragem no domínio discreto, são apresentados e analisados. São também descritas teorias de processos de montagem e soldagem de placas eletrônicas com objetivo de definir uma metodologia de projeto, montagem e soldagem de placas eletrônicas. Tal metodologia é aplicada no projeto e manufatura do protótipo de um módulo de filtragem digital para repetidores de telefonia celular. O projeto, implementado usando FPGA, é baseado nos dois sistemas supracitados. Ao final do texto, resultados obtidos em experimentos de filtragem digital e reconstrução de sinais em frequência intermediária com o protótipo desenvolvido são apresentados.

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ABSTRACT: The thermal entry region in laminar forced convection of Herschel-Bulkley fluids is solved analytically through the integral transform technique, for both circular and parallel-plates ducts, which are maintained at a prescribed wall temperature or at a prescribed wall heat flux. The local Nusselt numbers are obtained with high accuracy in both developing and fully-developed thermal regions, and critical comparisons with previously reported numerical results are performed.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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This paper presents a Computer Aided Diagnosis (CAD) system that automatically classifies microcalcifications detected on digital mammograms into one of the five types proposed by Michele Le Gal, a classification scheme that allows radiologists to determine whether a breast tumor is malignant or not without the need for surgeries. The developed system uses a combination of wavelets and Artificial Neural Networks (ANN) and is executed on an Altera DE2-115 Development Kit, a kit containing a Field-Programmable Gate Array (FPGA) that allows the system to be smaller, cheaper and more energy efficient. Results have shown that the system was able to correctly classify 96.67% of test samples, which can be used as a second opinion by radiologists in breast cancer early diagnosis. (C) 2013 The Authors. Published by Elsevier B.V.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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In many movies of scientific fiction, machines were capable of speaking with humans. However mankind is still far away of getting those types of machines, like the famous character C3PO of Star Wars. During the last six decades the automatic speech recognition systems have been the target of many studies. Throughout these years many technics were developed to be used in applications of both software and hardware. There are many types of automatic speech recognition system, among which the one used in this work were the isolated word and independent of the speaker system, using Hidden Markov Models as the recognition system. The goals of this work is to project and synthesize the first two steps of the speech recognition system, the steps are: the speech signal acquisition and the pre-processing of the signal. Both steps were developed in a reprogrammable component named FPGA, using the VHDL hardware description language, owing to the high performance of this component and the flexibility of the language. In this work it is presented all the theory of digital signal processing, as Fast Fourier Transforms and digital filters and also all the theory of speech recognition using Hidden Markov Models and LPC processor. It is also presented all the results obtained for each one of the blocks synthesized e verified in hardware

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The increasing amount of sequences stored in genomic databases has become unfeasible to the sequential analysis. Then, the parallel computing brought its power to the Bioinformatics through parallel algorithms to align and analyze the sequences, providing improvements mainly in the running time of these algorithms. In many situations, the parallel strategy contributes to reducing the computational complexity of the big problems. This work shows some results obtained by an implementation of a parallel score estimating technique for the score matrix calculation stage, which is the first stage of a progressive multiple sequence alignment. The performance and quality of the parallel score estimating are compared with the results of a dynamic programming approach also implemented in parallel. This comparison shows a significant reduction of running time. Moreover, the quality of the final alignment, using the new strategy, is analyzed and compared with the quality of the approach with dynamic programming.

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Sao Paulo State Research Foundation-FAPESP