Filtragem adaptativa aplicada à redução de desvios em séries temporais de previsão numérica climática.

Esta dissertação apresenta resultados da aplicação de filtros adaptativos, utilizando os algoritmos NLMS (Normalized Least Mean Square) e RLS (Recursive Least Square), para a redução de desvios em previsões climáticas. As discrepâncias existentes entre o estado real da atmosfera e o previsto por um modelo numérico tendem a aumentar ao longo do período de integração. O modelo atmosférico Eta é utilizado operacionalmente para previsão numérica no CPTEC/INPE e como outros modelos atmosféricos, apresenta imprecisão nas previsões climáticas. Existem pesquisas que visam introduzir melhorias no modelo atmosférico Eta e outras que avaliam as previsões e identificam os erros do modelo para que seus produtos sejam utilizados de forma adequada. Dessa forma, neste trabalho pretende-se filtrar os dados provenientes do modelo Eta e ajustá-los, de modo a minimizar os erros entre os resultados fornecidos pelo modelo Eta e as reanálises do NCEP. Assim, empregamos técnicas de processamento digital de sinais e imagens com o intuito de reduzir os erros das previsões climáticas do modelo Eta. Os filtros adaptativos nesta dissertação ajustarão as séries ao longo do tempo de previsão. Para treinar os filtros foram utilizadas técnicas de agrupamento de regiões, como por exemplo o algoritmo de clusterização k-means, de modo a selecionar séries climáticas que apresentem comportamentos semelhantes entre si. As variáveis climáticas estudadas são o vento meridional e a altura geopotencial na região coberta pelo modelo de previsão atmosférica Eta com resolução de 40 km, a um nível de pressão de 250 hPa. Por fim, os resultados obtidos mostram que o filtro com 4 coeficientes, adaptado pelo algoritmo RLS em conjunto com o critério de seleção de regiões por meio do algoritmo k-means apresenta o melhor desempenho ao reduzir o erro médio e a dispersão do erro, tanto para a variável vento meridional quanto para a variável altura geopotencial.

Transient photoconductivity and its light-induced change of lightly boron-doped a-Si : H films

Transient photoconductivity and its light-induced change were investigated by using a Model 4400 boxcar averager and signal processor for lightly boron-doped a-Si : H films. The transient photoconductivities of the sample were measured at an annealed state and light-soaked states. The transient decay process of the photoconductivity can be fitted fairly well by a second-order exponential decay function, which indicates that the decay process is related with two different traps. It is noteworthy that the photoconductivity of the film increases after light-soaking. This may be due to the deactivity of the boron acceptor B-4(-), and thus some of the boron atoms can no longer act as acceptors and drives E-F to shifts upward. Consequently, the number of effective recombination centers may be reduced and so the photoconductivity increases.

A multi-standard active-RC filter with accurate tuning system

A low-power, highly linear, multi-standard, active-RC filter with an accurate and novel tuning architec-ture is presented. It exhibits 1EEE 802. 11a/b/g (9.5 MHz) and DVB-H (3 MHz, 4 MHz) application. The filter exploits digitally-controlled polysilicon resistor banks and a phase lock loop type automatic tuning system. The novel and complex automatic frequency calibration scheme provides better than 4 comer frequency accuracy, and it can be powered down after calibration to save power and avoid digital signal interference. The filter achieves OIP3 of 26 dBm and the measured group delay variation of the receiver filter is 50 ns (WLAN mode). Its dissipation is 3.4 mA in RX mode and 2.3 mA (only for one path) in TX mode from a 2.85 V supply. The dissipation of calibration consumes 2 mA. The circuit has been fabricated in a 0.35μm 47 GHz SiGe BiCMOS technology; the receiver and transmitter filter occupy 0.21 mm~2 and 0.11 mm~2 (calibration circuit excluded), respectively.

用VHDL实现的23位快速浮点数加减法器

With the development of LSI, FPGA/CPLD has been used more and more in the fields of digital signal processing and au-tocontrol and so on. And with the development of the techniques of digital processing, for fitting the system’s function, it should be a higher requirement to speed and used-resource to compute the floating point numbers. The author introduces a high speed adder-subtracter of the 23 bit’s floating point numbers, which is carried out with the parallel arithmetic and the computational speed cou...中文文摘：随着大规模集成电路的不断发展,FPGA/CPLD在数字信号处理、自动控制等方面得到了越来越多的应用。并且伴随着数字化处理技术的不断发展,为满足系统功能的要求,对浮点数运算的速度以及相应占用的资源也就提出了更高的要求。笔者即介绍了以VHDL语言为基础,采用并行算法且计算速度达到33MHz的,对23位标准浮点数实现的高速浮点加减法运算器,并以Cyclone II芯片EP2C20F484为硬件环境,最终进行时序模拟仿真,从而验证该浮点加减法器的正确性和快速特性。

微型ROV控制装置及控制方法

介绍了一种基于嵌入式ARM9技术的微型ROV的控制装置及控制方法。该装置可以同时进行两通道串行通讯,实现微型ROV的视频信号、潜水深度、艏向角度、纵倾角度、横摇角度、电子舱温度等数据的采集和与上位机的通讯传输;该装置可以采集16路模拟量信号和12路数字量信号,输出4路模拟量信号和12路TTL电平信号,实现推进器、水下灯、水下摄像机、云台等ROV功能器件的驱动。该装置具有通讯能力强、集成度高、功耗低等特点,可以满足微型ROV所有的常用功能要求。

嵌入式智能图像处理在火灾预警系统的应用

传统的火灾检测方法一般采用感烟、感温、感光探测器等进行探测。本文提出了一种嵌入式基于图像视觉特征的火灾检测方法,以TI公司的数字多媒体处理器TMS320DM642为核心,设计实现智能前端火灾探测与自动报警系统。通过DM642对视频图像进行采集并结合相应的智能图像处理与模式识别算法,对森林火险进行实时监控。实验结果表明,该系统比传统系统更进一步减少了误报率且具有响应快、监控范围广等优点。

A Comparison of Hardware Implementations for Low-Level Vision Algorithms

Early and intermediate vision algorithms, such as smoothing and discontinuity detection, are often implemented on general-purpose serial, and more recently, parallel computers. Special-purpose hardware implementations of low-level vision algorithms may be needed to achieve real-time processing. This memo reviews and analyzes some hardware implementations of low-level vision algorithms. Two types of hardware implementations are considered: the digital signal processing chips of Ruetz (and Broderson) and the analog VLSI circuits of Carver Mead. The advantages and disadvantages of these two approaches for producing a general, real-time vision system are considered.

A Binocular, Foveated Active Vision System

This report documents the design and implementation of a binocular, foveated active vision system as part of the Cog project at the MIT Artificial Intelligence Laboratory. The active vision system features a three degree of freedom mechanical platform that supports four color cameras, a motion control system, and a parallel network of digital signal processors for image processing. To demonstrate the capabilities of the system, we present results from four sample visual-motor tasks.

Determining WWW User's Next Access and Its Application to Pre-fetching

World-Wide Web (WWW) services have grown to levels where significant delays are expected to happen. Techniques like pre-fetching are likely to help users to personalize their needs, reducing their waiting times. However, pre-fetching is only effective if the right documents are identified and if user's move is correctly predicted. Otherwise, pre-fetching will only waste bandwidth. Therefore, it is productive to determine whether a revisit will occur or not, before starting pre-fetching. In this paper we develop two user models that help determining user's next move. One model uses Random Walk approximation and the other is based on Digital Signal Processing techniques. We also give hints on how to use such models with a simple pre-fetching technique that we are developing.