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We demonstrate a compact multi-resonant metamaterial structure based on integrated U- and T-shaped nano-aperture antennas. We investigate the physical origin of the multi-resonant behavior and determine the parameter dependence of the nano-aperture antennas both experimentally and numerically. We also show enhanced field distribution in the apertures at the corresponding resonance wavelengths. Both multi-spectral response and enhanced near field distributions can open up exciting new opportunities in applications ranging from subwavelength optics and optoelectronics to chemical and biosensing.
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We propose an all-optical method to actively control the transmission of nanoslit arrays for scanning and lensing applications. We show that by utilizing two lateral control slits, the transmitted beam can be actively steered.
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A novel inverse halftoning method is proposed to restore a continuous tone image from a given half-tone image. A set theoretic formulation is used where three sets are defined using the prior information about the problem. A new space-domain projection is introduced assuming the halftoning is performed using error diffusion, and the error diffusion filter kernel is known. The space-domain, frequency-domain, and space-scale domain projections are used alternately to obtain a feasible solution for the inverse halftoning problem which does not have a unique solution.
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This work characterizes the dynamics of sleep spindles, observed in electroencephalogram (EEG) recorded from humans during sleep, using both time and frequency domain methods which depend on higher order statistics and spectra. The time domain method combines the use of second- and third-order correlations to reveal information on the stationarity of periodic spindle rhythms to detect transitions between multiple activities. The frequency domain method, based on normalized spectrum and bispectrum, describes frequency interactions associated with nonlinearities occurring in the observed EEG.
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Eletroencefalografia/estatística & dados numéricos , Fases do Sono/fisiologia , Adulto , Engenharia Biomédica , Humanos , Modelos Biológicos , Dinâmica não Linear , PeriodicidadeRESUMO
Subband decomposition techniques have been extensively used for data coding and analysis. In most filter banks, the goal is to obtain subsampled signals corresponding to different spectral regions of the original data. However, this approach leads to various artifacts in images having spatially varying characteristics, such as images containing text, subtitles, or sharp edges. In this paper, adaptive filter banks with perfect reconstruction property are presented for such images. The filters of the decomposition structure which can be either linear or nonlinear vary according to the nature of the signal. This leads to improved image compression ratios. Simulation examples are presented.
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In polyacrylamide gel electrophoresis (PAGE) image analysis, it is important to determine the percentage of the protein of interest of a protein mixture. This study presents reliable computer software to determine this percentage. The region of interest containing the protein band is detected using the snake algorithm. The iterative snake algorithm is implemented in a multi-resolutional framework. The snake is initialized on a low-resolution image. Then, the final position of the snake at the low resolution is used as the initial position in the higher-resolution image. Finally, the area of the protein is estimated as the area enclosed by the final position of the snake.
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Algoritmos , Eletroforese em Gel de Poliacrilamida/métodos , Processamento de Imagem Assistida por Computador , Densitometria/métodos , Proteínas/análise , SoftwareRESUMO
In this work, a subband domain textual image compression method is developed. The document image is first decomposed into subimages using binary subband decompositions. Next, the character locations in the subbands and the symbol library consisting of the character images are encoded. The method is suitable for keyword search in the compressed data. It is observed that very high compression ratios are obtained with this method. Simulation studies are presented.
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Most color image printing and display devices do not have the capability of reproducing true color images. A common remedy is the use of dithering techniques that take advantage of the lower sensitivity of the eye to spatial resolution and exchange higher color resolution with lower spatial resolution. An adaptive error diffusion method for color images is presented. The error diffusion filter coefficients are updated by a normalized least mean square-type (LMS-type) algorithm to prevent textural contours, color impulses, and color shifts, which are among the most common side effects of the standard dithering algorithms. Another novelty of the new method is its vector character: previous applications of error diffusion have treated the individual color components of an image separately. We develop a general vector approach and demonstrate through simulation studies that superior results are achieved.
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In this paper, a multilead ECG data compression method is presented. First, a linear transform is applied to the standard ECG lead signals which are highly correlated with each other. In this way a set of uncorrelated transform domain signals is obtained. Then, resulting transform domain signals are compressed using various coding methods, including multirate signal processing and transform domain coding techniques.