This paper describes a study of noise robust voice activity detection (VAD) utilizing the periodic component to aperiodic component ratio (PAR). Although environmental sound changes dynamically in the real world, conventional noise robust features for VAD are sensitive to the non-stationarity of noise, which yields variations in the signal to noise ratio, and sometimes requires apriori noise po...

Noise-induced firing is studied in two major classes of bursting neuron models in the absence of periodic input. In the biologically relevant subthreshold regime where no deterministic firing occurs, additive noise induces spiking limit cycles. This noise makes the output firing patterns sensitive to the characteristics of autonomous subthreshold oscillations, which can change in response to va...

This paper deals with the identification of errors–in–variables (EIV) models corrupted by additive and uncorrelated white Gaussian noises when the noise–free input is an arbitrary signal, not necessarily periodic. In particular, a frequency domain maximum likelihood (ML) estimator is proposed. As some other EIV estimators, this method assumes that the ratio of the noise variances is known.

The effects of intrinsic spontaneous-emission noise on the nonlinear dynamics of an optically injected semiconductor laser is quantitatively studied through a single-mode model. It is found that for periodic motions, the effect of this noise source is to kick phase points off the underlying deterministic limit cycle. When the noise is not too strong so that phase points can stay near the limit ...

This paper presents a new single channel noise reduction method for suppressing periodic alarm noise in telephony speech. The presence of background alarm noise can significantly detract from the intelligibility of telephony speech received by emergency services, and in particular, by the fire brigade control rooms. The attraction of the proposed approach is that it targets the alarm noise with...

We study noise-induced resonance effects in the leaky integrate-and-fire neuron model with absolute refractory period, driven by a Gaussian white noise. It is demonstrated that a finite noise level may either maximize or minimize the regularity of the spike train. We also partition the parameter space into regimes where either or both of these effects occur. It is shown that the coherence minim...