51 resultados para filter cake


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Combined tunable WDM converters based on SiC multilayer photonic active filters are analyzed. The operation combines the properties of active long-pass and short-pass wavelength filter sections into a capacitive active band-pass filter. The sensor element is a multilayered heterostructure produced by PE-CVD. The configuration includes two stacked SiC p-i-n structures sandwiched between two transparent contacts. Transfer function characteristics are studied both theoretically and experimentally. Results show that optical bias activated photonic device combines the demultiplexing operation with the simultaneous photodetection and self amplification of an optical signal acting the device as an integrated photonic filter in the visible range. Depending on the wavelength of the external background and irradiation side, the device acts either as a short- or a long-pass band filter or as a band-stop filter. The output waveform presents a nonlinear amplitude-dependent response to the wavelengths of the input channels. A numerical simulation and a two building-blocks active circuit are presented and give insight into the physics of the device. (c) 2013 Elsevier B.V. All rights reserved.

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Red, green and blue optical signals were directed to an a-SiC:H multilayered device, each one with a specific transmission rate. The combined optical signal was analyzed by reading out, under different applied voltages, the generated photocurrent. Results show that when a chromatic time dependent wavelength combination with different transmission rates irradiates the multilayered structure, the device operates as a tunable wavelength filter and can be used in wavelength division multiplexing systems for short range communications. An application to fluorescent proteins detection is presented. (C) 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

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Wireless local-area networks (WLANs) have been deployed as office and home communications infrastructures worldwide. The diversification of the standards, such as IEEE 802.11 series demands the design of RF front-ends. Low power consumption is one of the most important design concerns in the application of those technologies. To maintain competitive hardware costs, CMOS has been used since it is the best solution for low cost and high integration processing, allowing analog circuits to be mixed with digital ones. In the receiver chain, the low noise amplifier (LNA) is one of the most critical blocks in a transceiver design. The sensitivity is mainly determined by the LNA noise figure and gain. It interfaces with the pre-select filter and the mixer. Furthermore, since it is the first gain stage, care must be taken to provide accurate input match, low-noise figure, good linearity and a sufficient gain over a wide band of operation. Several CMOS LNAs have been reported during the last decade, showing that the most research has been done at 802.11/b and GSM standards (900-2400MHz spectrum) and more recently at 802.11/a (5GHz band). One of the more significant disadvantages of 802.11/b is that the frequency band is crowded and subject to interference from other technologies, as is 2.4GHz cordless phones and Bluetooth. As the demand for radio-frequency integrated circuits, operating at higher frequency bands, increases, the IEEE 802.11/a standard becomes a very attractive option to wireless communication system developers. This paper presents the design and implementation of a low power, low noise amplifier aimed at IEEE 802.11a for WLAN applications. It was designed to be integrated with an active balun and mixer, representing the first step toward a fully integrated monolithic WLAN receiver. All the required circuits are integrated at the same die and are powered by 1.8V supply source. Preliminary experimental results (S-parameters) are shown and promise excellent results. The LNA circuit design details are illustrated in Section 2. Spectre simulation results focused at gain, noise figure (NF) and input/output matching are presented in Section 3. Finally, conclusions and comparison with other recently reported LNAs are made in Section 4, followed by future work.

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Research on the problem of feature selection for clustering continues to develop. This is a challenging task, mainly due to the absence of class labels to guide the search for relevant features. Categorical feature selection for clustering has rarely been addressed in the literature, with most of the proposed approaches having focused on numerical data. In this work, we propose an approach to simultaneously cluster categorical data and select a subset of relevant features. Our approach is based on a modification of a finite mixture model (of multinomial distributions), where a set of latent variables indicate the relevance of each feature. To estimate the model parameters, we implement a variant of the expectation-maximization algorithm that simultaneously selects the subset of relevant features, using a minimum message length criterion. The proposed approach compares favourably with two baseline methods: a filter based on an entropy measure and a wrapper based on mutual information. The results obtained on synthetic data illustrate the ability of the proposed expectation-maximization method to recover ground truth. An application to real data, referred to official statistics, shows its usefulness.

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Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Automação e Electrónica Industrial

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In this paper we demonstrate an add/drop filter based on SiC technology. Tailoring of the channel bandwidth and wavelength is experimentally demonstrated. The concept is extended to implement a 1 by 4 wavelength division multiplexer with channel separation in the visible range. The device consists of a p-i'(a-SiC:H)-n/p-i(a-Si: H)-n heterostructure. Several monochromatic pulsed lights, separately or in a polychromatic mixture illuminated the device. Independent tuning of each channel is performed by steady state violet bias superimposed either from the front and back sides. Results show that, front background enhances the light-to-dark sensitivity of the long and medium wavelength channels and quench strongly the others. Back violet background has the opposite behaviour. This nonlinearity provides the possibility for selective removal or addition of wavelengths. An optoelectronic model is presented and explains the light filtering properties of the add/drop filter, under different optical bias conditions.

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This paper presents the recent research results about the development of a Observed Time Difference (OTD) based geolocation algorithm based on network trace data, for a real Universal Mobile Telecommunication System (UMTS) Network. The initial results have been published in [1], the current paper focus on increasing the sample convergence rate, and introducing a new filtering approach based on a moving average spatial filter, to increase accuracy. Field tests have been carried out for two radio environments (urban and suburban) in the Lisbon area, Portugal. The new enhancements produced a geopositioning success rate of 47% and 31%, and a median accuracy of 151 m and 337 m, for the urban and suburban environments, respectively. The implemented filter produced a 16% and 20% increase on accuracy, when compared with the geopositioned raw data. The obtained results are rather promising in accuracy and geolocation success rate. OTD positioning smoothed by moving average spatial filtering reveals a strong approach for positioning trace extracted events, vital for boosting Self-Organizing Networks (SON) over a 3G network.

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A noncoherent vector delay/frequency-locked loop (VDFLL) architecture for GNSS receivers is proposed. A bank of code and frequency discriminators feeds a central extended Kalman filter that estimates the receiver's position and velocity, besides the clock error. The VDFLL architecture performance is compared with the one of the classic scalar receiver, both for scintillation and multipath scenarios, in terms of position errors. We show that the proposed solution is superior to the conventional scalar receivers, which tend to lose lock rapidly, due to the sudden drops of the received signal power.

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We analyze the advantages and drawbacks of a vector delay/frequency-locked loop (VDFLL) architecture regarding the conventional scalar and the vector delay-locked loop (VDLL) architectures for GNSS receivers in harsh scenarios that include ionospheric scintillation, multipath, and high dynamics motion. The VDFLL is constituted by a bank of code and frequency discriminators feeding a central extended Kaiman filter (EKF) that estimates the receiver's position, velocity, and clock bias. Both code and frequency loops are closed vectorially through the EKF. The VDLL closes the code loop vectorially and the phase loops through individual PLLs while the scalar receiver closes both loops by means of individual independent PLLs and DLLs.

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Expanding far beyond traditional applications at telecommunications wavelengths, the SiC photonic devices has recently proven its merits for working with visible range optical signals. Reconfigurable wavelength selectors are essential sub-systems for implementing reconfigurable WDM networks and optical signal processing. Visible range to telecom band spectral translation in SiC/Si can be accomplished using wavelength selector under appropriated optical bias, acting as reconfigurable active filters. In this paper we present a monolithically integrated wavelength selector based on a multilayer SiC/Si integrated optical filters that requires optical switches to select wavelengths. The selector filter is realized by using double pin/pin a-SiC:H photodetector with front and back biased optical gating elements. Red, green, blue and violet communication channels are transmitted together, each one with a specific bit sequence. The combined optical signal is analyzed by reading out the generated photocurrent, under different background wavelengths applied either from the front or the back side. The backgrounds acts as channel selectors that selects one or more channels by splitting portions of the input multi-channel optical signals across the front and back photodiodes. The transfer characteristics effects due to changes in steady state light, irradiation side and frequency are presented. The relationship between the optical inputs and the digital output levels is established. (C) 2014 Elsevier B.V. All rights reserved.

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Visible range to telecom band spectral translation is accomplished using an amorphous SiC pi'n/pin wavelength selector under appropriate front and back optical light bias. Results show that background intensity works as selectors in the infrared region, shifting the sensor sensitivity. Low intensities select the near-infrared range while high intensities select the visible part according to its wavelength. Here, the optical gain is very high in the infrared/red range, decreases in the green range, stays close to one in the blue region and strongly decreases in the near-UV range. The transfer characteristics effects due to changes in steady state light intensity and wavelength backgrounds are presented. The relationship between the optical inputs and the output signal is established. A capacitive optoelectronic model is presented and tested using the experimental results. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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In this paper the viability of an integrated wavelength optical filter and photodetector for visible light communication (VLC) is discussed. The proposed application uses indoor warm light lamps lighting accomplished by ultra-bright light-emitting diodes (LEDs) pulsed at frequencies higher than the ones perceived by the human eye. The system was analyzed at two different wavelengths in the visible spectrum (430 nm and 626 nm) with variable optical intensities. The signals were transmitted into free space and measured using a multilayered photodetector based on a-SiC:H/a-Si:H. The detector works as an optical filter with controlled wavelength sensitivity through the use of optical bias. The output photocurrent was measured for different optical intensities of the transmitted optical signal and the extent of each signal was tested. The influence of environmental fluorescent lighting was also analysed in order to test the strength of the system. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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In this paper, we present a multilayer device based on a-Si:H/a-SiC:H that operates as photodetector and optical filter. The use of such device in protein detection applications is relevant in Fluorescence Resonance Energy Transfer (FRET) measurements. This method demands the detection of fluorescent signals located at specific wavelengths bands in the visible part of the electromagnetic spectrum. The device operates in the visible range with a selective sensitivity dependent on electrical and optical bias. Several nanosensors were tested with a commercial spectrophotometer to assess the performance of FRET signals using glucose solutions of different concentrations. The proposed device was used to demonstrate the possibility of FRET signals detection, using visible signals of similar wavelength and intensity. The device sensitivity was tuned to enhance the wavelength band of interest using steady state optical bias at 400 nm. Results show the ability of the device to detect signals in this range. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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This paper presents a new predictive digital control method applied to Matrix Converters (MC) operating as Unified Power Flow Controllers (UPFC). This control method, based on the inverse dynamics model equations of the MC operating as UPFC, just needs to compute the optimal control vector once in each control cycle, in contrast to direct dynamics predictive methods that needs 27 vector calculations. The theoretical principles of the inverse dynamics power flow predictive control of the MC based UPFC with input filter are established. The proposed inverse dynamics predictive power control method is tested using Matlab/Simulink Power Systems toolbox and the obtained results show that the designed power controllers guarantees decoupled active and reactive power control, zero error tracking, fast response times and an overall good dynamic and steady-state response.

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Feature selection is a central problem in machine learning and pattern recognition. On large datasets (in terms of dimension and/or number of instances), using search-based or wrapper techniques can be cornputationally prohibitive. Moreover, many filter methods based on relevance/redundancy assessment also take a prohibitively long time on high-dimensional. datasets. In this paper, we propose efficient unsupervised and supervised feature selection/ranking filters for high-dimensional datasets. These methods use low-complexity relevance and redundancy criteria, applicable to supervised, semi-supervised, and unsupervised learning, being able to act as pre-processors for computationally intensive methods to focus their attention on smaller subsets of promising features. The experimental results, with up to 10(5) features, show the time efficiency of our methods, with lower generalization error than state-of-the-art techniques, while being dramatically simpler and faster.