In this paper, a new method is proposed in order to evaluate the stochastic solution of linear random differential equation. The method is based on the combination of the probabili...
Abstract. For many statistical pattern recognition methods, distributions of sample vectors are assumed to be normal, and the quadratic discriminant function derived from the proba...
This document describes a method for classifying images of blood cells. Three different classes of cells are used: Band Neutrophils, Eosinophils and Lymphocytes. The image pattern...
This article describes a new model of probability density function and its use in estimation of distribution algorithms. The new model, the distribution tree, has interesting prope...
A Gaussian mixture model (GMM) estimates a probability density function using the expectation-maximization algorithm. However, it may lead to a poor performance or inconsistency. T...
- In this paper, we show how a topographic mapping can be created from a product of experts. We learn the parameters of the mapping using gradient descent on the negative logarithm...
An architecture and implementation of a high performance Gaussian random number generator (GRNG) is described. The GRNG uses the Ziggurat algorithm which divides the area under th...
Guanglie Zhang, Philip Heng Wai Leong, Dong-U Lee,...
This paper proposes an optimisation to the UK-means algorithm, which generalises the k-means algorithm to handle objects whose locations are uncertain. The location of each object...
— In bit interleaved coded modulation (BICM), the probability density function (PDF) of the reliability metrics (Lvalues) fully defines the BICM transmission and may be used to ...
In this article, a new method for performance evaluation of Turbo-like codes is presented. This is based on estimating the Probability Density Function (pdf) of the bit Log-Likelih...