126 resultados para Signal de transduction

em Cambridge University Engineering Department Publications Database


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This paper details the design and enhanced electrical transduction of a bulk acoustic mode resonator fabricated in a commercial foundry MEMS process utilizing 2.5 μm gaps. The I-V characteristics of electrically addressed silicon resonators are often dominated by capacitive parasitics, inherent to hybrid technologies. This paper benchmarks a variety of drive and detection principles for electrostatically driven square-extensional mode resonators operating in air via analytical models accompanied by measurements of fabricated devices with the primary aim of enhancing the ratio of the motional to feedthrough current at nominal operating voltages. In view of ultimately enhancing the motional to feedthrough current ratio, a new detection technique that combines second harmonic capacitive actuation and piezoresistive detection is presented herein. This new method is shown to outperform previously reported methods utilizing voltages as low as ±3 V in air, providing a promising solution for low voltage CMOS-MEMS integration. To elucidate the basis of this improvement in signal output from measured devices, an approximate analytical model for piezoresistive sensing specific to the resonator topology reported here is also developed and presented. © 2010 Elsevier B.V. All rights reserved.

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Electrically addressed silicon bulk acoustic wave microresonators offer high Q solutions for applications in sensing and signal processing. However, the electrically transduced motional signal is often swamped by parasitic feedthrough in hybrid technologies. With the aim of enhancing the ratio of the motional to feedthrough current at nominal operating voltages, this paper benchmarks a variety of drive and detection principles for electrostatically driven square-extensional mode resonators operating in air and in a foundry MEMS process utilizing 2μm gaps. A new detection technique, combining second harmonic capacitive actuation and piezoresistive detection, outperforms previously reported methods utilizing voltages as low as ± 3V in air providing a promising solution for low voltage CMOS-MEMS integration. ©2009 IEEE.

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The separation of independent sources from mixed observed data is a fundamental and challenging problem. In many practical situations, observations may be modelled as linear mixtures of a number of source signals, i.e. a linear multi-input multi-output system. A typical example is speech recordings made in an acoustic environment in the presence of background noise and/or competing speakers. Other examples include EEG signals, passive sonar applications and cross-talk in data communications. In this paper, we propose iterative algorithms to solve the n × n linear time invariant system under two different constraints. Some existing solutions for 2 × 2 systems are reviewed and compared.

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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.

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