Traditional investigations with evolutionary programming (EP) for continuous parameter optimization problems have used a single mutation operator with a parameterized probability density function (pdf), typically a Gaussian. Using a variety of mutation operators that can be combined during evolution to generate pdf’s of varying shapes could hold the potential for producing better solutions with...

An improvement on the voice detection algorithm using global soft decision (GSD) is made in this paper. In GSD method, the speech and noise are modelled by the presumed probability density function, e.g. Gaussian pdf. We propose that the estimation and modelling of the signal is done in the domain of filterbank output which widely used in most speech processing applications. Since the output of...

In this paper detection performances of the Bayesian Optimum Radar Detector (BORD) against nonGaussian ground clutter data are showed in the case of an unknown complex amplitude target. Recalling first how BORD was derived from the non-Gaussian SIRP model (Spherically Invariant Random Process) clutter we derive theoretical performances of the asymptotical expression of BORD which is CFAR with r...

In this paper, we propose a new speech probability distribution, two-sided generalized gamma distribution (GΓD) for an efficient parametric characterization of speech spectra. GΓD forms a generalized class of parametric distributions including the Gaussian, Laplacian and Gamma probability density functions (pdf’s) as special cases. All the parameters associated with the GΓD are estimated by the...

In this paper, we propose a new speech probability distribution, two-sided generalized gamma distribution (GΓD) for an efficient parametric characterization of speech spectra. GΓD forms a generalized class of parametric distributions including the Gaussian, Laplacian and Gamma probability density functions (pdf’s) as special cases. All the parameters associated with the GΓD are estimated by the...

Particle filters are ensemble-based assimilation schemes that, unlike the ensemble Kalman filter, employ a fully nonlinear and non-Gaussian analysis step to compute the probability distribution function (pdf) of a system’s state conditioned on a set of observations. Evidence is provided that the ensemble size required for a successful particle filter scales exponentially with the problem size. ...

The local, uncorrelated multiplicative noises driving a second-order, purely noise-induced, ordering phase transition (NIPT) were assumed to be Gaussian and white in the model of [Phys. Rev. Lett. 73, 3395 (1994)]. The potential scientific and technological interest of this phenomenon calls for a study of the effects of the noises’ statistics and spectrum. This task is facilitated if these nois...

It is essential to have deep understanding of the mobile radio channel in particular for radio communication modeling and advanced technology system design. Models for the mobile radio channel are vital for the study of smart antenna systems, both for the design of algorithms, systemtesting purposes, and for network planning. This paper provides an intensive study of the spatial characteristics...

Bucklew’s high-rate vector quantizer mismatch result is extended from fixed-rate coding to variable-rate coding using a Lagrangian formulation. It is shown that if an asymptotically (high-rate) optimal sequence of variable rate codes is designed for a -dimensional probability density function (pdf) and then applied to another pdf for which is bounded, then the resulting mismatch or loss of perf...

We study the quasilinear evolution of the one-point probability density functions (PDFs) of the smoothed density and velocity fields in a cosmological gravitating system beginning with Gaussian initial fluctuations. Our analytic results are based on the Zel’dovich approximation and laminar flow. A numerical analysis extends the results into the multistreaming regime using the smoothed fields of...