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This paper proposes a probabilistic collocation method (PCM) to quantify the uncertainties in state estimation. Comparing to classic Monte-Carlo (MC) method, the proposed PCM is based on sparse grid points and uses a smaller number of sparse grid points to quantify the uncertainty. Thus, the proposed PCM can quantify a large number of uncertain power system variables with relatively lower computational...
The semi-quantitative simulations were outlined at the beginning of the paper which presented an improved numerical interval simulation algorithm introducing probability density function to interval semi-quantitative simulation. The uncertain parameters were represented by probability density functions (pdf) in the novel algorithm instead of intervals. The pdf of uncertain parameter can be determined...
A shared memory parallel computer system can be considered as a parallel computer system with a shared single ready queue. This can depict a single queue parallel server queuing model. Some models that are based on probability density function have been used to model the performance of the queuing system. This paper uses recursive to evaluate the performance of a single queue parallel server queuing...
In this paper, we focus on the modeling of wideband single-input single-output (SISO) mobile fading channels for indoor propagation environments. The derived indoor reference channel model is based on a geometrical scattering model, which consists of an infinite number of scatterers uniformly distributed over the two-dimensional (2D) horizontal plane of a rectangular room. We derive analytical expressions...
The probability density function (PDF) optimized quantization has been shown to be more efficient than the conventional quantization methods. In practical application, the data with bounded support can be modelled better with bounded support distribution (e.g. beta distribution, Dirichlet distribution) and a better quantization performance could be achieved by a more reasonable modelling. In this...
This paper introduces Copula approach, which has been widely used in statistical field, to the construction of OLAP cubes for the first time. Based on this approach, a novel scheme is proposed to compress data and answer any OLAP query without accessing raw data. The procedure of this scheme can be generally divided into three steps. Firstly, find the proper distribution functions to fit the marginal...
Inspired from the mechanism of Fuzzy C-means (FCMs) which introduces a degree of fuzziness on the dissimilarity function based on distances, a fuzzy Expectation Maximization (EM) algorithm for Gaussian Mixture Models (GMMs) is proposed in this paper. In the fuzzy EM algorithm, the dissimilarity function is defined as the multiplicative inverse of probability density function. Different from FCMs,...
PC-SVM is a new developed support vector machine classifier with probabilistic constrains which presence of samples probability in each class is determined based on a distribution function. The presence of noise causes incorrect calculation of support vectors thereupon margin can not be maximized. In the Pc-SVM, constraints boundaries and constraints occurrence have probability density functions which...
This paper deals with the design and simulation of narrowband indoor propagation channels under line-of-sight (LOS) and non-LOS (NLOS) propagation conditions. We propose a reference channel model assuming that the scatterers are uniformly distributed in the two-dimensional (2D) horizontal space of a room. We derive analytical expressions for the probability density function (PDF) of the angle-of-arrival...
In this paper, we improve the real-time object tracking algorithm of Yang [1] which uses a symmetric similarity function between spatially smoothed kernel-density estimates of the model and the target distributions. This spatial smoothed process applied on the centre points of the probability density functions increases not only computational complexity but also noise sensitivity. After reducing background...
Stationary properties of node distribution and speed distribution for random direction model were studied. Firstly, geometric probability was applied to analyze stationary node distribution. A closed form probability density function for circular regions was obtained which indicated that mobile nodes tended to disperse with simulation advancing. Secondly, we applied palm calculus to calculate probability...
Agent based technologies have become more and more widespread during the last few years and the number of practical applications has noticeable increased, especially in the new Grid Computing paradigm. Grid Computing system implementations are easily transferable into Cluster Grid environments. So, the main purpose of this research is to validate integration functionalities and performances of an...
The p-values observed in independent tests on some hypothesis are, under the overall null hypothesis, a sample from the standard uniform. Thus uniformity tests are an important tool in meta-analysis, and the family of probability density functions {fxm(x) = (mx - (m-2)/2) I(0,1)(x), m ∈ [-2, 0]} provides an interesting theoretical framework to assess uniformity. In fact, H0: m = 0 stands for uniformity,...
Several data management applications rely on data clustering methods which are usually designed to handle a static object as a single point in space. In recent years, clustering static objects seems to reach a stable point. Clustering uncertain objects is more challenging than clustering static objects and currently, it is actively studied in data mining clustering researches. In this paper, we study...
The real world is composed of sets of objects that move and morph in both space and time. Useful concepts can be defined in terms of the complex interactions between the multi-dimensional attributes of subsets of these objects and of the relationships that exist between them. In this paper, we present spatiotemporal multi-dimensional relational framework (SMRF) trees, a new data mining technique that...
Discovering episodes, frequent sets of events from a sequence has been an active field in pattern mining. Traditionally, a level-wise approach is used to discover all frequent episodes. While this technique is computationally feasible it may result in a vast number of patterns, especially when low thresholds are used. In this paper we propose a new quality measure for episodes. We say that an episode...
We propose a modified discrete HMM that handles multimodalities. We assume that the feature space is partitioned into subspaces generated by different sources of information. To combine these heteregoneous modalities we propose a multi-stream discrete HMM that assigns a relevance weight to each subspace. The relevance weights are set local and depend on the symbols and the states. In particular, we...
The layered mobility model architecture, as introduced earlier, provides a framework for the construction of microscopic mobility models for wireless network simulations. In this paper, we are continuing our study of the architecture and provide the fundamental results necessary for the definition and analysis of theoretic models. This is done for the first time for such rich mobility framework, allowing...
In this paper, a simplified channel model for land mobile satellite systems (LMSS) is proposed, which makes use of Ricean fading for the line-of-sight (LOS) scenario and composite Nakagami-m/Gamma fading for the shadowed scenario. The closed form expressions for the probability density function (pdf) and the moment generating function for the signal strength are derived. The proposed model is shown...
An accurate model for analyzing the performance of wireless land mobile satellite (LMS) communication systems is the shadowed-Rice (SR) fading model. In this paper, new simple expressions for the probability density function (PDF) and the cumulative distribution function (CDF) of the sum of possibly correlated non identically distributed squared SR random variables are derived. To this end, a novel...
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