44 resultados para Audio amplifiers


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In this paper, analysis and synthesis approach for two new variants within the Class-EF power amplifier (PA) family is elaborated. These amplifiers are classified here as Class-E3 F2 and transmission-line (TL) Class-E3 F 2. The proposed circuits offer means to alleviate some of the major issues faced by existing topologies such as substantial power losses due to the parasitic resistance of the large inductor in the Class-EF load network and deviation from ideal Class-EF operation due to the effect of device output inductance at high frequencies. Both lumped-element and transmission-line load networks for the Class-E 3 F PA are described. The load networks of the Class-E3 F and TL Class-E 3 F2amplifier topologies developed in this paper simultaneously satisfy the Class-EF optimum impedance requirements at fundamental frequency, second, and third harmonics as well as simultaneously providing matching to the circuit optimum load resistance for any prescribed system load resistance. Optimum circuit component values are analytically derived and validated by harmonic balance simulations. Trade-offs between circuit figures of merit and component values with some practical limitations being considered are discussed. © 2010 IEEE.

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Coupling of a soft X-ray laser beam with a relaying concave mirror in a sequentially pumped amplifier geometry using the Ne-like Ge system has been studied experimentally. Preliminary observations indicate an increase in the spatial coherence of the amplified relayed beam. In addition, near-field imaging of one of the amplifier plasmas shows a double-lobed intensity pattern of the emergent beam indicating refractive guiding of the amplified beam with components both normal and tangential to the target surface.

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The Audio/Visual Emotion Challenge and Workshop (AVEC 2011) is the first competition event aimed at comparison of multimedia processing and machine learning methods for automatic audio, visual and audiovisual emotion analysis, with all participants competing under strictly the same conditions. This paper first describes the challenge participation conditions. Next follows the data used – the SEMAINE corpus – and its partitioning into train, development, and test partitions for the challenge with labelling in four dimensions, namely activity, expectation, power, and valence. Further, audio and video baseline features are introduced as well as baseline results that use these features for the three sub-challenges of audio, video, and audiovisual emotion recognition.