Search results for "Correlation"
showing 10 items of 2282 documents
Application of Statistical Process Control to Continuous Processes
2002
Control charts represent an efficient and easy tool to assure the state of statistical quality control in a manufacturing process. These tools are also implemented in continuous processes, where the critical parameters are often monitored by on line sensors measuring data with short time intervals. In this paper a continuous process is monitored by using control charts and its dynamic is modeled through linear time series that allow the effects of the autocorrelation to be eliminated. In this way, the control charts can operate on residuals that result identically and independently distributed. A statistical analysis on EWMA, CUSUM and control charts for individual measurements has been car…
A non-stationary multipath fading channel model incorporating the effect of velocity variations of the mobile station
2014
A standard assumption in mobile fading channel modelling is that the mobile station (MS) moves along a straight line with constant speed. In practice, this assumption is violated in most propagation scenarios. For the development of more realistic channel models, it is therefore important to relax this restriction by allowing the MS to change its velocity. In this paper, we study the effect of velocity changes on the statistical properties of multipath fading channels. Expressions will be derived for the local autocorrelation function (ACF), the Wigner-Ville spectrum, the average Doppler shift, and the Doppler spread. Our findings show that a variation of the speed and/or the direction of t…
Non-linear Invertible Representation for Joint Statistical and Perceptual Feature Decorrelation
2000
The aim of many image mappings is representing the signal in a basis of decorrelated features. Two fundamental aspects must be taken into account in the basis selection problem: data distribution and the qualitative meaning of the underlying space. The classical PCA techniques reduce the statistical correlation using the data distribution. However, in applications where human vision has to be taken into account, there are perceptual factors that make the feature space uneven, and additional interaction among the dimensions may arise. In this work a common framework is presented to analyse the perceptual and statistical interactions among the coefficients of any representation. Using a recen…
Phase Fourier vector model for scale invariant three-dimensional image detection.
2009
A scale invariant 3D object detection method based on phase Fourier transform (PhFT) is addressed. Three-dimensionality is expressed in terms of range images. The PhFT of a range image gives information about the orientations of the surfaces in the 3D object. When the object is scaled, the PhFT becomes a distribution multiplied by a constant factor which is related to the scale factor. Then 3D scale invariant detection can be solved as illumination invariant detection process. Several correlation operations based on vector space representation are applied. Results show the tolerance of detection method to scale besides discrimination against false objects.
Modeling and statistical characterization of wideband indoor radio propagation channels
2010
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 for the probability density function (PDF) of the angle of arrival (AOA), the power delay profile (PDP), and the frequency correlation function (FCF). An efficient sum-of-cisoids (SOC) channel simulator will be derived from the proposed non-realizable reference model. It is shown that the …
Clustering categorical data: A stability analysis framework
2011
Clustering to identify inherent structure is an important first step in data exploration. The k-means algorithm is a popular choice, but K-means is not generally appropriate for categorical data. A specific extension of k-means for categorical data is the k-modes algorithm. Both of these partition clustering methods are sensitive to the initialization of prototypes, which creates the difficulty of selecting the best solution for a given problem. In addition, selecting the number of clusters can be an issue. Further, the k-modes method is especially prone to instability when presented with ‘noisy’ data, since the calculation of the mode lacks the smoothing effect inherent in the calculation …
A statistical monitoring approach for automotive on-board diagnostic systems
2007
The current generation of vehicle models are increasingly being equipped with on-board diagnostic (OBD) systems aimed at assessing the ‘state of health’ of important anti-pollution subsystems and components. In order to promptly diagnose and fix quality and reliability problems that may potentially affect such complex diagnostic systems, even during advanced development prior to mass production, some vehicle prototypes undergo a testing phase under realistic conditions of use (a mileage accumulation campaign). The aim of this work is to set up a statistical tool for improving the reliability of the OBD system by monitoring its operation during the mileage accumulation campaign of a new vehi…
Cooperative compressive power spectrum estimation in wireless fading channels
2017
This paper considers multiple wireless sensors that cooperatively estimate the power spectrum of the signals received from several sources. We extend our previous work on cooperative compressive power spectrum estimation to accommodate the scenario where the statistics of the fading channels experienced by different sensors are different. The signals received from the sources are assumed to be time-domain wide-sense stationary processes. Multiple sensors are organized into several groups, where each group estimates a different subset of lags of the temporal correlation. A fusion centre (FC) combines these estimates to obtain the power spectrum. As each sensor group computes correlation esti…
A methodology to assess the intrinsic discriminative ability of a distance function and its interplay with clustering algorithms for microarray data …
2013
Abstract Background Clustering is one of the most well known activities in scientific investigation and the object of research in many disciplines, ranging from statistics to computer science. Following Handl et al., it can be summarized as a three step process: (1) choice of a distance function; (2) choice of a clustering algorithm; (3) choice of a validation method. Although such a purist approach to clustering is hardly seen in many areas of science, genomic data require that level of attention, if inferences made from cluster analysis have to be of some relevance to biomedical research. Results A procedure is proposed for the assessment of the discriminative ability of a distance functi…
Can SQ and EQ Values and Their Difference Indicate Programming Aptitude to Reduce Dropout Rate?
2017
A crucial problem that we are currently facing at the Faculty of Computing of the University of Latvia is that during the first study semester on average 30% of the first-year students drop out, whereas after the first year of studies the number of dropouts increases up to nearly 50%. Thus, our overall goal is to determine in advance applicants that most likely will not finish the first study year successfully. A hypothesis formulated in another research study was that programming aptitude could be predicted based on the results of two personality self-report questionnaires − Systemizing Quotient (SQ) and Empathy Quotient (EQ) − taken by students. The difference between the SQ and EQ scores…