145 resultados para local enhancement

em Cambridge University Engineering Department Publications Database


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We report a detailed study of surface-bound chemical vapor deposition of carbon nanotubes and nanofibers from evaporated transition metal catalysts exposed to ammonia diluted acetylene. We show that a reduction of the Fe/Co catalyst film thickness below 3 nm results into a transition from large diameter (> 40 nm), bamboo-like nanofibers to small diameter (similar to 5 nm) multi-walled carbon nanotubes. The nanostructuring of ultrathin catalyst films critically depends on the gas atmosphere, with the resulting island distribution initiating the carbon nucleation. Compared to purely thermal chemical vapor deposition, we find that, for small diameter nanotube growth, DC plasma assistance is detrimental to graphitization and sample homogeneity and cannot prevent an early catalyst poisoning. (c) 2006 Elsevier B.V. All rights reserved.

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Hydrogen rearrangements at the H*2 complex are used as a model of low energy, local transitions in the two-hydrogen density of states of hydrogenated amorphous silicon (a-Si:H). These are used to account for the low activation energy motion of H observed by nuclear magnetic resonance, the low energy defect annealing of defects formed by bias stress in thin film transistors, and the elimination of hydrogen from the growth zone during the low temperature plasma deposition of a-Si:H. © 1998 Elsevier Science B.V. All rights reserved.

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We present a statistical model-based approach to signal enhancement in the case of additive broadband noise. Because broadband noise is localised in neither time nor frequency, its removal is one of the most pervasive and difficult signal enhancement tasks. In order to improve perceived signal quality, we take advantage of human perception and define a best estimate of the original signal in terms of a cost function incorporating perceptual optimality criteria. We derive the resultant signal estimator and implement it in a short-time spectral attenuation framework. Audio examples, references, and further information may be found at http://www-sigproc.eng.cam.ac.uk/~pjw47.