905 resultados para Fpga devices
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The ubiquity and power of personal digital devices make them attractive tools for STEM instructors who would like to stimulate active learning. These devices offer both abundant pedagogical opportunities and worrisome challenges. We will discuss our two years of experience in using mobile devices to teach biology in a community college setting, as well as our observations on the best ways to organize digital-based activities to facilitate student active learning.
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This essay has identified and analysed rhetorical devices in Gordon Brown’s speech delivered at the Labour Party conference on September 25, 2006. The aim of the study was to identify specific rhetorical devices which are described as interactional resources, analyse their uses and discuss possible effects that they may have when included in a political speech. The results are based on my own interpretations but are supported by information provided in current literature by analysts and researchers of rhetoric use. The result findings could probably serve as evidence of the need for better understanding of the devices used by politicians in their relentless endeavours to influence audience decisions.
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This dissertation is focused on theoretical and experimental studies of optical properties of materials and multilayer structures composing liquid crystal displays (LCDs) and electrochromic (EC) devices. By applying spectroscopic ellipsometry, we have determined the optical constants of thin films of electrochromic tungsten oxide (WOx) and nickel oxide (NiOy), the films’ thickness and roughness. These films, which were obtained at spattering conditions possess high transmittance that is important for achieving good visibility and high contrast in an EC device. Another application of the general spectroscopic ellipsometry relates to the study of a photo-alignment layer of a mixture of azo-dyes SD-1 and SDA-2. We have found the optical constants of this mixture before and after illuminating it by polarized UV light. The results obtained confirm the diffusion model to explain the formation of the photo-induced order in azo-dye films. We have developed new techniques for fast characterization of twisted nematic LC cells in transmissive and reflective modes. Our techniques are based on the characteristics functions that we have introduced for determination of parameters of non-uniform birefringent media. These characteristic functions are found by simple procedures and can be utilised for simultaneous determination of retardation, its wavelength dispersion, and twist angle, as well as for solving associated optimization problems. Cholesteric LCD that possesses some unique properties, such as bistability and good selective scattering, however, has a disadvantage – relatively high driving voltage (tens of volts). The way we propose to reduce the driving voltage consists of applying a stack of thin (~1µm) LC layers. We have studied the ability of a layer of a surface stabilized ferroelectric liquid crystal coupled with several retardation plates for birefringent color generation. We have demonstrated that in order to accomplish good color characteristics and high brightness of the display, one or two retardation plates are sufficient.
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This thesis presents the study and development of fault-tolerant techniques for programmable architectures, the well-known Field Programmable Gate Arrays (FPGAs), customizable by SRAM. FPGAs are becoming more valuable for space applications because of the high density, high performance, reduced development cost and re-programmability. In particular, SRAM-based FPGAs are very valuable for remote missions because of the possibility of being reprogrammed by the user as many times as necessary in a very short period. SRAM-based FPGA and micro-controllers represent a wide range of components in space applications, and as a result will be the focus of this work, more specifically the Virtex® family from Xilinx and the architecture of the 8051 micro-controller from Intel. The Triple Modular Redundancy (TMR) with voters is a common high-level technique to protect ASICs against single event upset (SEU) and it can also be applied to FPGAs. The TMR technique was first tested in the Virtex® FPGA architecture by using a small design based on counters. Faults were injected in all sensitive parts of the FPGA and a detailed analysis of the effect of a fault in a TMR design synthesized in the Virtex® platform was performed. Results from fault injection and from a radiation ground test facility showed the efficiency of the TMR for the related case study circuit. Although TMR has showed a high reliability, this technique presents some limitations, such as area overhead, three times more input and output pins and, consequently, a significant increase in power dissipation. Aiming to reduce TMR costs and improve reliability, an innovative high-level technique for designing fault-tolerant systems in SRAM-based FPGAs was developed, without modification in the FPGA architecture. This technique combines time and hardware redundancy to reduce overhead and to ensure reliability. It is based on duplication with comparison and concurrent error detection. The new technique proposed in this work was specifically developed for FPGAs to cope with transient faults in the user combinational and sequential logic, while also reducing pin count, area and power dissipation. The methodology was validated by fault injection experiments in an emulation board. The thesis presents comparison results in fault coverage, area and performance between the discussed techniques.
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O crescente avanço nas mais diversas áreas da eletrônica, desde instrumentação em baixa freqüência até telecomunicações operando em freqüências muito elevadas, e a necessidade de soluções baratas em curto espaço de tempo que acompanhem a demanda de mercado, torna a procura por circuitos programáveis, tanto digitais como analógicos, um ponto comum em diversas pesquisas. Os dispositivos digitais programáveis, que têm como grande representante os Field Programmable Gate Arrays (FPGAs), vêm apresentando um elevado e contínuo crescimento em termos de complexidade, desempenho e número de transistores integrados, já há várias décadas. O desenvolvimento de dispositivos analógicos programáveis (Field Programmable Analog Arrays – FPAAs), entretanto, esbarra em dois pontos fundamentais que tornam sua evolução um tanto latente: a estreita largura de banda alcançada, conseqüência da necessidade de um grande número de chaves de programação e reconfiguração, e a elevada área consumida por componentes analógicos como resistores e capacitores, quando integrados em processos VLSI Este trabalho apresenta uma proposta para aumentar a faixa de freqüências das aplicações passíveis de serem utilizadas tanto em FPAAs comerciais quanto em outros FPAAs, através da utilização de uma interface de translação e seleção de sinais, mantendo características de programabilidade do FPAA em questão, sem aumentar em muito sua potência consumida. A proposta, a simulação e a implementação da interface são apresentadas ao longo desta dissertação. Resultados de simulação e resultados práticos obtidos comprovam a eficácia da proposta.
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O objectivo deste trabalho é a implementação em hardware de uma Rede Neuronal com um microprocessador embebido, podendo ser um recurso valioso em várias áreas científicas. A importância das implementações em hardware deve-se à flexibilidade, maior desempenho e baixo consumo de energia. Para esta implementação foi utilizado o dispositivo FPGA Virtex II Pro XC2VP30 com um MicroBlaze soft core, da Xilinx. O MicroBlaze tem vantagens como a simplicidade no design, sua reutilização e fácil integração com outras tecnologias. A primeira fase do trabalho consistiu num estudo sobre o FPGA, um sistema reconfigurável que possui características importantes como a capacidade de executar em paralelo tarefas complexas. Em seguida, desenvolveu-se o código de implementação de uma Rede Neuronal Artificial baseado numa linguagem de programação de alto nível. Na implementação da Rede Neuronal aplicou-se, na camada escondida, a função de activação tangente hiperbólica, que serve para fornecer a não linearidade à Rede Neuronal. A implementação é feita usando um tipo de Rede Neuronal que permite apenas ligações no sentido de saída, chamado Redes Neuronais sem realimentação (do Inglês Feedforward Neural Networks - FNN). Como as Redes Neuronais Artificiais são sistemas de processamento de informações, e as suas características são comuns às Redes Neuronais Biológicas, aplicaram-se testes na implementação em hardware e analisou-se a sua importância, a sua eficiência e o seu desempenho. E finalmente, diante dos resultados, fez-se uma análise de abordagem e metodologia adoptada e sua viabilidade.
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Supervisor: Ian Oakley
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O objetivo deste projeto foi o de realizar a sincronização de pelo menos quatro câmaras individuais, ajustando dinamicamente o frame rate de operação de cada câmara, tendo por base a família de sensores de imagem CMOS NanEye da empresa Awaiba, numa plataforma FPGA com interface USB3. Durante o projeto analisou-se, com a assistência de um supervisor da Awaiba, o sistema core de captura de imagem existente, baseado em VHDL. Foi estudado e compreendido o princípio do ajuste dinâmico do frame rate das câmaras. Tendo sido então desenvolvido o módulo de controlo da câmara, em VHDL, e um algoritmo de ajuste dinâmico do frame rate, sendo este implementado junto com a plataforma de processamento e interface da FPGA. Foi criado um módulo para efetuar a monitorização da frequência de operação de cada câmara, medindo o período de cada linha numa frame, tendo por base um sinal de relógio de valor conhecido. A frequência é ajustada variando o nível de tensão aplicado ao sensor com base no erro entre o período da linha medido e o período pretendido. Para garantir o funcionamento conjunto de múltiplas câmaras em modo síncrono foi implementada uma interface Master-Slave entre estas. Paralelamente ao módulo anteriormente descrito, implementou-se um sistema de controlo automático de iluminação com base na análise de regiões de interesse em cada frame captada por uma câmara NanEye. A intensidade de corrente aplicada às fontes de iluminação acopladas à câmara é controlada dinamicamente com base no nível de saturação dos pixéis analisados em cada frame. Foram desenvolvidas e implementadas variantes do algoritmo de controlo e o seu desempenho foi avaliado em laboratório. Os resultados obtidos na prática evidenciam que a solução implementada cumpre os requisitos de controlo e ajuste da frequência de operação de múltiplas câmaras. Mostrou ser um método de controlo capaz de manter um erro de sincronização médio de 3,77 μs mesmo na presença de variações de temperatura de aproximadamente 50 °C. Foi também demonstrado que o sistema de controlo de iluminação é capaz de proporcionar uma experiência de visualização adequada, alcançando erros menores que 3% e uma velocidade de ajuste máxima inferior a 1 s.
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The semiconductor technologies evolutions leads devices to be developed with higher processing capability. Thus, those components have been used widely in more fields. Many industrial environment such as: oils, mines, automotives and hospitals are frequently using those devices on theirs process. Those industries activities are direct related to environment and health safe. So, it is quite important that those systems have extra safe features yield more reliability, safe and availability. The reference model eOSI that will be presented by this work is aimed to allow the development of systems under a new view perspective which can improve and make simpler the choice of strategies for fault tolerant. As a way to validate the model na architecture FPGA-based was developed.
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This study shows the implementation and the embedding of an Artificial Neural Network (ANN) in hardware, or in a programmable device, as a field programmable gate array (FPGA). This work allowed the exploration of different implementations, described in VHDL, of multilayer perceptrons ANN. Due to the parallelism inherent to ANNs, there are disadvantages in software implementations due to the sequential nature of the Von Neumann architectures. As an alternative to this problem, there is a hardware implementation that allows to exploit all the parallelism implicit in this model. Currently, there is an increase in use of FPGAs as a platform to implement neural networks in hardware, exploiting the high processing power, low cost, ease of programming and ability to reconfigure the circuit, allowing the network to adapt to different applications. Given this context, the aim is to develop arrays of neural networks in hardware, a flexible architecture, in which it is possible to add or remove neurons, and mainly, modify the network topology, in order to enable a modular network of fixed-point arithmetic in a FPGA. Five synthesis of VHDL descriptions were produced: two for the neuron with one or two entrances, and three different architectures of ANN. The descriptions of the used architectures became very modular, easily allowing the increase or decrease of the number of neurons. As a result, some complete neural networks were implemented in FPGA, in fixed-point arithmetic, with a high-capacity parallel processing
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This work proposes hardware architecture, VHDL described, developed to embedded Artificial Neural Network (ANN), Multilayer Perceptron (MLP). The present work idealizes that, in this architecture, ANN applications could easily embed several different topologies of MLP network industrial field. The MLP topology in which the architecture can be configured is defined by a simple and specifically data input (instructions) that determines the layers and Perceptron quantity of the network. In order to set several MLP topologies, many components (datapath) and a controller were developed to execute these instructions. Thus, an user defines a group of previously known instructions which determine ANN characteristics. The system will guarantee the MLP execution through the neural processors (Perceptrons), the components of datapath and the controller that were developed. In other way, the biases and the weights must be static, the ANN that will be embedded must had been trained previously, in off-line way. The knowledge of system internal characteristics and the VHDL language by the user are not needed. The reconfigurable FPGA device was used to implement, simulate and test all the system, allowing application in several real daily problems
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A challenge that remains in the robotics field is how to make a robot to react in real time to visual stimulus. Traditional computer vision algorithms used to overcome this problem are still very expensive taking too long when using common computer processors. Very simple algorithms like image filtering or even mathematical morphology operations may take too long. Researchers have implemented image processing algorithms in high parallelism hardware devices in order to cut down the time spent in the algorithms processing, with good results. By using hardware implemented image processing techniques and a platform oriented system that uses the Nios II Processor we propose an approach that uses the hardware processing and event based programming to simplify the vision based systems while at the same time accelerating some parts of the used algorithms