985 resultados para field programmable gate array


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Hyperspectral instruments have been incorporated in satellite missions, providing large amounts of data of high spectral resolution of the Earth surface. This data can be used in remote sensing applications that often require a real-time or near-real-time response. To avoid delays between hyperspectral image acquisition and its interpretation, the last usually done on a ground station, onboard systems have emerged to process data, reducing the volume of information to transfer from the satellite to the ground station. For this purpose, compact reconfigurable hardware modules, such as field-programmable gate arrays (FPGAs), are widely used. This paper proposes an FPGA-based architecture for hyperspectral unmixing. This method based on the vertex component analysis (VCA) and it works without a dimensionality reduction preprocessing step. The architecture has been designed for a low-cost Xilinx Zynq board with a Zynq-7020 system-on-chip FPGA-based on the Artix-7 FPGA programmable logic and tested using real hyperspectral data. Experimental results indicate that the proposed implementation can achieve real-time processing, while maintaining the methods accuracy, which indicate the potential of the proposed platform to implement high-performance, low-cost embedded systems, opening perspectives for onboard hyperspectral image processing.

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The main goal of the present Master’s Thesis project was to create a field-programmable gate array (FPGA) based system for the control of single-electron transistors or other cryoelectronic devices. The FPGA and similar technologies are studied in the present work. The fixed and programmable logic are compared with each other. The main features and limitations of the hardware used in the project are investigated. The hardware and software connections of the device to the computer are shown in detail. The software development techniques for FPGA-based design are described. The steps of design for programmable logic are considered. Furthermore, the results of filters implemented in the software are illustrated.

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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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The move from Standard Definition (SD) to High Definition (HD) represents a six times increases in data, which needs to be processed. With expanding resolutions and evolving compression, there is a need for high performance with flexible architectures to allow for quick upgrade ability. The technology advances in image display resolutions, advanced compression techniques, and video intelligence. Software implementation of these systems can attain accuracy with tradeoffs among processing performance (to achieve specified frame rates, working on large image data sets), power and cost constraints. There is a need for new architectures to be in pace with the fast innovations in video and imaging. It contains dedicated hardware implementation of the pixel and frame rate processes on Field Programmable Gate Array (FPGA) to achieve the real-time performance. ^ The following outlines the contributions of the dissertation. (1) We develop a target detection system by applying a novel running average mean threshold (RAMT) approach to globalize the threshold required for background subtraction. This approach adapts the threshold automatically to different environments (indoor and outdoor) and different targets (humans and vehicles). For low power consumption and better performance, we design the complete system on FPGA. (2) We introduce a safe distance factor and develop an algorithm for occlusion occurrence detection during target tracking. A novel mean-threshold is calculated by motion-position analysis. (3) A new strategy for gesture recognition is developed using Combinational Neural Networks (CNN) based on a tree structure. Analysis of the method is done on American Sign Language (ASL) gestures. We introduce novel point of interests approach to reduce the feature vector size and gradient threshold approach for accurate classification. (4) We design a gesture recognition system using a hardware/ software co-simulation neural network for high speed and low memory storage requirements provided by the FPGA. We develop an innovative maximum distant algorithm which uses only 0.39% of the image as the feature vector to train and test the system design. Database set gestures involved in different applications may vary. Therefore, it is highly essential to keep the feature vector as low as possible while maintaining the same accuracy and performance^

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This paper presents a new approach to develop Field Programmable Analog Arrays (FPAAs),(1) which avoids excessive number of programming elements in the signal path, thus enhancing the performance. The paper also introduces a novel FPAA architecture, devoid of the conventional switching and connection modules. The proposed FPAA is based on simple current mode sub-circuits. An uncompounded methodology has been employed for the programming of the Configurable Analog Cell (CAC). Current mode approach has enabled the operation of the FPAA presented here, over almost three decades of frequency range. We have demonstrated the feasibility of the FPAA by implementing some signal processing functions.

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This paper presents a novel self-timed multi-purpose sensor especially conceived for Field Programmable Gate Arrays (FPGAs). The aim of the sensor is to measure performance variations during the life-cycle of the device, such as process variability, critical path timing and temperature variations. The proposed topology, through the use of both combinational and sequential FPGA elements, amplifies the time of a signal traversing a delay chain to produce a pulse whose width is the sensor’s measurement. The sensor is fully self-timed, avoiding the need for clock distribution networks and eliminating the limitations imposed by the system clock. One single off- or on-chip time-to-digital converter is able to perform digitization of several sensors in a single operation. These features allow for a simplified approach for designers wanting to intertwine a multi-purpose sensor network with their application logic. Employed as a temperature sensor, it has been measured to have an error of ±0.67 °C, over the range of 20–100 °C, employing 20 logic elements with a 2-point calibration.

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This paper presents the design and the prototype implementation of a three-phase power inverter developed to drive a motor-in-wheel. The control system is implemented in a FPGA (Field Programmable Gate Array) device. The paper describes the Field Oriented Control (FOC) algorithm and the Space Vector Modulation (SVM) technique that were implemented. The control platform uses a Spartan-3E FPGA board, programmed with Verilog language. Simulation and experimental results are presented to validate the developed system operation under different load conditions. Finally are presented conclusions based on the experimental results.

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How can a bridge be built between autonomic computing approaches and parallel computing systems? The work reported in this paper is motivated towards bridging this gap by proposing a swarm-array computing approach based on ‘Intelligent Agents’ to achieve autonomy for distributed parallel computing systems. In the proposed approach, a task to be executed on parallel computing cores is carried onto a computing core by carrier agents that can seamlessly transfer between processing cores in the event of a predicted failure. The cognitive capabilities of the carrier agents on a parallel processing core serves in achieving the self-ware objectives of autonomic computing, hence applying autonomic computing concepts for the benefit of parallel computing systems. The feasibility of the proposed approach is validated by simulation studies using a multi-agent simulator on an FPGA (Field-Programmable Gate Array) and experimental studies using MPI (Message Passing Interface) on a computer cluster. Preliminary results confirm that applying autonomic computing principles to parallel computing systems is beneficial.

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Os dispositivos analógicos programáveis (FPAAs, do inglês, Field Programmable Analog Arrays), apesar de ainda não terem a mesma popularidade de seus pares digitais (FPGAs, do inglês, Field Programmable Gate Arrays), possuem uma gama de aplicações bastante ampla, que vai desde o condicionamento de sinais em sistemas de instrumentação, até o processamento de sinais de radiofreqüência (RF) em telecomunicações. Porém, ao mesmo tempo em que os FPAAs trouxeram um impressionante ganho na agilidade de concepção de circuitos analógicos, também trouxeram um conjunto de novos problemas relativos ao teste deste tipo de dispositivo. Os FPAAs podem ser divididos em duas partes fundamentais: seus blocos programáveis básicos (CABs, do inglês, Configurable Analog Blocks) e sua rede de interconexões. A rede de interconexões, por sua vez, pode ser dividida em duas partes: interconexões internas (locais e globais entre CABs) e interconexões externas (envolvendo células de I/O). Todas estas partes apresentam características estruturais e funcionais distintas, de forma que devem ser testadas separadamente, pois necessitam que se considerem modelos de falhas, configurações e estímulos de teste específicos para assegurar uma boa taxa de detecção de defeitos. Como trabalhos anteriores já estudaram o teste dos CABs, o foco desta dissertação está direcionado ao desenvolvimento de metodologias que se propõem a testar a rede de interconexões de FPAAs. Apesar das várias diferenças entre as redes de interconexões de FPGAs e FPAAs, muitas também são as semelhanças entre elas, sendo, portanto, indiscutível que o ponto de partida deste trabalho tenha que ser o estudo das muitas técnicas propostas para o teste de interconexões em FPGAs, para posterior adaptação ao caso dos FPAAs. Além disto, embora o seu foco não recaia sobre o teste de CABs, pretende-se utilizá-los como recursos internos do dispositivo passíveis de gerar sinais e analisar respostas de teste, propondo uma abordagem de auto-teste integrado de interconexões que reduza o custo relativo ao equipamento externo de teste. Eventualmente, estes mesmos recursos poderão também ser utilizados para diagnóstico das partes defeituosas. Neste trabalho, utiliza-se como veículo de experimentação um dispositivo específico (Anadigm AN10E40), mas pretende-se que as metodologias de teste propostas sejam abrangentes e possam ser facilmente adaptadas a outros FPAAs comerciais que apresentem redes de interconexão semelhantes.

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In this paper is proposed and analyzed a digital hysteresis modulation using a FPGA (Field Programmable Gate Array) device and VHDL (Hardware Description Language), applied at a hybrid three-phase rectifier with almost unitary input power factor, composed by parallel SEPIC controlled single-phase rectifiers connected to each leg of a standard 6-pulses uncontrolled diode rectifier. The digital control allows a programmable THD (Total Harmonic Distortion) at the input currents, and it makes possible that the power rating of the switching-mode converters, connected in parallel, can be a small fraction of the total average output power, in order to obtain a compact converter, reduced input current THD and almost unitary input power factor. The proposed digital control, using a FPGA device and VHDL, offers an important flexibility for the associated control technique, in order to obtain a programmable PFC (Power Factor Correction) hybrid three-phase rectifier, in agreement with the international standards (IEC, and IEEE), which impose limits for the THD of the AC (Alternate Current) line input currents. Finally, the proposed control strategy is verified through experimental results from an implemented prototype. ©2008 IEEE.

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In this paper is proposed and analyzed a digital hysteresis modulation using a FPGA (Field Programmable Gate Array) device and VHDL (Hardware Description Language), applied at a hybrid three-phase rectifier with almost unitary input power factor, composed by parallel SEPIC controlled single-phase rectifiers connected to each leg of a standard 6-pulses uncontrolled diode rectifier. The digital control allows a programmable THD (Total Harmonic Distortion) at the input currents, and it makes possible that the power rating of the switching-mode converters, connected in parallel, can be a small fraction of the total average output power, in order to obtain a compact converter, reduced input current THD and almost unitary input power factor. Finally, the proposed digital control, using a FPGA device and VHDL, offers an important flexibility for the associated control technique, in order to obtain a programmable PFC (Power Factor Correction) hybrid three-phase rectifier, in agreement with the international standards (IEC, and IEEE), which impose limits for the THD of the AC (Alternate Current) line input currents. The proposed strategy is verified by experiments. © 2008 IEEE.

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The main objective of this work is to present an efficient method for phasor estimation based on a compact Genetic Algorithm (cGA) implemented in Field Programmable Gate Array (FPGA). To validate the proposed method, an Electrical Power System (EPS) simulated by the Alternative Transients Program (ATP) provides data to be used by the cGA. This data is as close as possible to the actual data provided by the EPS. Real life situations such as islanding, sudden load increase and permanent faults were considered. The implementation aims to take advantage of the inherent parallelism in Genetic Algorithms in a compact and optimized way, making them an attractive option for practical applications in real-time estimations concerning Phasor Measurement Units (PMUs).

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O presente trabalho consiste na implementação em hardware de unidades funcionais dedicadas e optimizadas, para a realização das operações de codificação e descodificação, definidas na norma de codificação com perda Joint Photographic Experts Group (JPEG), ITU-T T.81 ISO/IEC 10918-1. Realiza-se um estudo sobre esta norma de forma a caracterizar os seus principais blocos funcionais. A finalidade deste estudo foca-se na pesquisa e na proposta de optimizações, de forma a minimizar o hardware necessário para a realização de cada bloco, de modo a que o sistema realizado obtenha taxas de compressão elevadas, minimizando a distorção obtida. A redução de hardware de cada sistema, codificador e descodificador, é conseguida à custa da manipulação das equações dos blocos Forward Discrete Cosine Transform (FDCT) e Quantificação (Q) e dos blocos Forward Discrete Cosine Transform (IDCT) e Quantificação Inversa (IQ). Com as conclusões retiradas do estudo e através da análise de estruturas conhecidas, descreveu-se cada bloco em Very-High-Speed Integrated Circuits (VHSIC) Hardware Description Language (VHDL) e fez-se a sua síntese em Field Programmable Gate Array (FPGA). Cada sistema implementado recorre à execução de cada bloco em paralelo de forma a optimizar a codificação/descodificação. Assim, para o sistema codificador, será realizada a operação da FDCT e Quantificação sobre duas matrizes diferentes e em simultâneo. O mesmo sucede para o sistema descodificador, composto pelos blocos Quantificação Inversa e IDCT. A validação de cada bloco sintetizado é executada com recurso a vectores de teste obtidos através do estudo efectuado. Após a integração de cada bloco, verificou-se que, para imagens greyscale de referência com resolução de 256 linhas por 256 colunas, é necessário 820,5 μs para a codificação de uma imagem e 830,5 μs para a descodificação da mesma. Considerando uma frequência de trabalho de 100 MHz, processam-se aproximadamente 1200 imagens por segundo.

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Relatório do Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Electrónica e Telecomunicações

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Trabalho de Projeto para obtenção do grau de Mestre em Engenharia de Eletrónica e Telecomunicações