A novel SOA-based crosspoint switch for mixed signal distribution

A 3x3 SOA-based switch is demonstrated for routing both radio-over-fiber and digital signals simultaneously. High extinction ratio digital baseband signals are transmitted and sufficient linearity is found for high performance RF signal distribution. © 2006 Optical Society of America.

Operation of a high frequency piezoelectric ultrasound array with an application specific integrated circuit

Integration of a piezoelectric high frequency ultrasound (HFUS) array with a microfabricated application specific integrated circuit (ASIC) performing a range of functions has several advantages for ultrasound imaging. The number of signal cables between the array/electronics and the data acquisition / imaging system can be reduced, cutting costs and increasing functionality. Electrical impedance matching is also simplified and the same approach can reduce overall system dimensions for applications such as endoscopic ultrasound. The work reported in this paper demonstrates early ASIC operation with a piezocomposite HFUS array operating at approximately 30 MHz. The array was tested in three different modes. Clear signals were seen in catch-mode, with an external transducer as a source of ultrasound, and in pitch-mode with the external transducer as a receiver. Pitch-catch mode was also tested successfully, using sequential excitation on three array elements, and viable signals were detected. However, these were relatively small and affected by interference from mixed-signal sources in the ASIC. Nevertheless, the functionality and compatibility of the two main components of an integrated HFUS - ASIC device have been demonstrated and the means of further optimization are evident.

Multi-channel signal separation

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.

Bayesian separation and recovery of convolutively mixed autoregressive sources

In this paper we address the problem of the separation and recovery of convolutively mixed autoregressive processes in a Bayesian framework. Solving this problem requires the ability to solve integration and/or optimization problems of complicated posterior distributions. We thus propose efficient stochastic algorithms based on Markov chain Monte Carlo (MCMC) methods. We present three algorithms. The first one is a classical Gibbs sampler that generates samples from the posterior distribution. The two other algorithms are stochastic optimization algorithms that allow to optimize either the marginal distribution of the sources, or the marginal distribution of the parameters of the sources and mixing filters, conditional upon the observation. Simulations are presented.

Mixed source model and its adapted vocal tract filter estimate for voice transformation and synthesis

In current methods for voice transformation and speech synthesis, the vocal tract filter is usually assumed to be excited by a flat amplitude spectrum. In this article, we present a method using a mixed source model defined as a mixture of the Liljencrants-Fant (LF) model and Gaussian noise. Using the LF model, the base approach used in this presented work is therefore close to a vocoder using exogenous input like ARX-based methods or the Glottal Spectral Separation (GSS) method. Such approaches are therefore dedicated to voice processing promising an improved naturalness compared to generic signal models. To estimate the Vocal Tract Filter (VTF), using spectral division like in GSS, we show that a glottal source model can be used with any envelope estimation method conversely to ARX approach where a least square AR solution is used. We therefore derive a VTF estimate which takes into account the amplitude spectra of both deterministic and random components of the glottal source. The proposed mixed source model is controlled by a small set of intuitive and independent parameters. The relevance of this voice production model is evaluated, through listening tests, in the context of resynthesis, HMM-based speech synthesis, breathiness modification and pitch transposition. © 2012 Elsevier B.V. All rights reserved.

MEMS-based mechanical AGC for oscillator circuits

This paper investigates a nonlinear amplitude saturation behavior in an electrostatically transduced, silicon MEMS disk resonator operating in its secondary elliptical bulk-mode (SEBM) at 3.932 MHz towards its implementation as an all-mechanical automatic gain control (AGC) element. The nonlinear vibration behavior of the SEBM mode is experimentally observed in open-loop testing such that above a threshold small signal drive voltage at a given polarization voltage, the vibration amplitude of the SEBM mode saturates. We also study this nonlinearity in an oscillator circuit designed such that the driving power level at the resonator input can be manually tuned as the circuit operates. The measurements of the voltage amplitudes show a clear transition from the linear to the nonlinear saturation region as the driving power is increased. Short-term frequency stability measurements were also conducted for different v ac and the resulting Allan deviation plots show an improvement in the short-term stability from 1.4 ppb in the linear region to 0.4 ppb in the amplitude saturation region. © 2013 IEEE.