In prior work, we developed a beamforming algorithm intended for automatic recognition of speech data captured with an array of distant microphones. In addition to enforcing a distortionless contraint in a desired direction, we adjusted the sensor weights so as to maximimize a negentropy criterion. Negentropy is a measure of how non-Gaussian the probability density function (pdf) of a random va...

Transforming complex multivariate geological data to be multivariate Gaussian is an important and challenging problem in geostatistics. A variety of transforms are available to accomplish this goal, but may struggle with data sets of high dimensional and sample sizes. Projection Pursuit Density Estimation (PPDE) is a well-established non-parametric method for estimating the joint PDF of multiva...

M. Nezamzadeh, I. Cameron Physics, Carleton University, Ottawa, ON, Canada, Radiology, The Ottawa Hospital, Ottawa, ON, Canada Introduction: It is well known that pixel intensities of magnitude MR images are biased by Rician noise [1-4]. This is particularly noticeable for SNR ≤ 2. Rician noise bias corrections from the literature [2,3] work well for SNR > 2 but not for SNR < 2. Furthermore, th...

In this paper, we extend the results for optimal transmission of the Gaussian channel state via the state-dependent channels to the communications of the Laplacian data. We derive a minimum mean square estimate (MMSE) of the stationary independent identically (i.i.d.) distributed Laplacian channel state corrupted by an additive white Gaussian noise (AWGN) and demonstrate that estimation accurac...

The traditional Bayesian estimator of short-time spectral amplitude is based on the minimization of the squared-error cost function under the common Gaussian probability density function (pdf). The Gaussian distribution, however, is not the optimal probability distribution. To overcome this phenomenon, we considered to replace the traditional distribution hypothesis of spectral amplitude of spe...

The tracking initiation problem is examined in the context of autonomous bearings-only-tracking (BOT) of a single appearing/disappearing target in the presence of clutter measurements. In general, this problem suffers from a combinatorial explosion in the number of potential tracks resulted from the uncertainty in the linkage between the target and the measurement (a.k.a the data association pr...

In this paper, a voice conversion approach that combines two distinct ideas is proposed to improve the converted-voice quality. The first idea is to map spectral features, e.g. discrete cepstrum coefficients (DCC), with segmental Gaussian mixture models (GMMs). That is, a single GMM of a large number of mixture components is replaced here with several voice-content specific GMMs each consisting...

Comparing the frequency of typical events with that of unusual events allows one to test whether the cosmological density distribution function is consistent with the normally made assumption of gaussianity. To this end, we compare the consistency of the tail-inferred (from clusters) and measured values (from largescale flows) of the rms level of mass fluctuations for two distribution functions...

There is strong evidence to suggest that data recorded from magnetoencephalography (MEG) follows a non-Gaussian distribution. However, existing standard methods for source localisation model the data using only second order statistics, and therefore use the inherent assumption of a Gaussian distribution. In this paper, we present a new general method for non-Gaussian source estimation of statio...

This article derives the probability density function (pdf) of the sum of a normal random variable and a (sphered) Student’s-t distribution on odd degrees of freedom greater than or equal to three. Apart from its intrinsic interest applications of this result include Bayesian wavelet shrinkage, Bayesian posterior density derivations, calculations in the theoretical analysis of projection indice...