Christophe Veaux

Instantaneous frequency estimation: Bayesian approaches versus reassignment-application to gravitational waves

Three new methods of instantaneous frequency estimation are introduced and compared in view of characterizing gravitational waves. Two methods are Bayesian and can be formulated as solutions of an ill-posed inverse problem with two different stochastic regularizations. Using either a state-space model for the time-frequency data or a compound non-uniform Bernoulli-Gauss model for the instantaneous frequency. The third method uses a reassignment technique applied to a spectrogram. In each case, averages based on different windowings permit to enhance the signal-to-noise ratio, leading to accurate results even below 0 dB.

Channel decoding using adaptive interframe and intraframe bit prediction in GSM system

The goal of source controlled channel decoding is to improve the performance of the channel decoder by using the residual redundancy of the speech encoded data. The original approach exploits only the interframe correlation between bits and few simple schemes have been devised in order to use the intraframe correlation. In this contribution, we present an efficient method to exploit the intraframe correlation during the channel decoding process. We predict the soft value of the bit being decoded from the bits already decoded along the trellis path. Our estimator of bit correlation is adaptively estimated from the soft bits values at the decoder output. Finally, the combination of interframe and intraframe prediction is applied to the full-rate and enhanced full-rate speech codecs in the GSM system.