Covariance Matrix Research Papers - Academia.edu (original) (raw)

ABSTRACT In this study, the figure condition method was introduced to analyse the accuracy of geometric correction. Figure condition denotes the transformation ability of estimated model parameters for a given transformation model, and it... more

ABSTRACT In this study, the figure condition method was introduced to analyse the accuracy of geometric correction. Figure condition denotes the transformation ability of estimated model parameters for a given transformation model, and it can be used in a geometric correction procedure. To study the figure condition, multisensor satellite images were geometrically corrected using ground control points obtained by different methods. The accuracy of each geometric model was analysed by means of the root mean square error of unit weight and variance–covariance matrix of unknown parameters. Then, an error propagation law was applied to the geometric model in order to investigate the transformation ability of the model parameters and estimate error values of geometric correction for the whole image surface. The results of the research demonstrated that the figure condition can be applied to geometric correction, and error values of the whole study area can be obtained with this new approach without using check points.

We present a method for estimating the mean vector from a multivariate skew dis-tribution that includes some unobserved data below the detection limits. The method uses a Box-Cox transformation, of which the parameters are found by... more

We present a method for estimating the mean vector from a multivariate skew dis-tribution that includes some unobserved data below the detection limits. The method uses a Box-Cox transformation, of which the parameters are found by maximizing the likelihood function ...

In this paper the authors show that the largest eigenvalue of the sample covariance matrix tends to a limit under certain conditions when both the number of variables and the sample size tend to infinity. The above result is proved under... more

In this paper the authors show that the largest eigenvalue of the sample covariance matrix tends to a limit under certain conditions when both the number of variables and the sample size tend to infinity. The above result is proved under the mild restriction that the fourth moment of the elements of the sample sums of squares and cross products (SP) matrix exist.

In this paper we introduce COV, a novel information retrieval (IR) algorithm for massive databases based on vector space modeling and spectral analysis of the covariance matrix, for the document vectors, to reduce the scale of the... more

In this paper we introduce COV, a novel information retrieval (IR) algorithm for massive databases based on vector space modeling and spectral analysis of the covariance matrix, for the document vectors, to reduce the scale of the problem. Since the dimension of the covariance matrix depends on the attribute space and is independent of the number of documents, COV can be applied to databases that are too massive for methods based on the singular value decomposition of the document-attribute matrix, such as latent semantic indexing (LSI). In addition to improved scalability, theoretical considerations indicate that results from our algorithm tend to be more accurate than those from LSI, particularly in detecting subtle differences in document vectors. We demonstrate the power and accuracy of COV through an important topic in data mining, known as outlier cluster detection. We propose two new algorithms for detecting major and outlier clusters in databases—the first is based on LSI, and the second on COV. Our implementation studies indicate that our cluster detection algorithms outperform the basic LSI and COV algorithm in detecting outlier clusters.

Formation of consumer basket is investigated by means of probability theory. Inflation on the consumer market can be managed by reducing its rate and lowering inflation-related risks. The approach is based on the treating the inflation... more

Formation of consumer basket is investigated by means of probability theory. Inflation on the consumer market can be managed by reducing its rate and lowering inflation-related risks. The approach is based on the treating the inflation risks of particular ingredients of the consumer goods basket as component of the whole complex rather than separate units. The proposed management strategy is focused on the degree of correlation between the rates of price increase of the items in the basket. Portfolio theories of Markowitz and Tobin are used.

The Dirichlet family owes its privileged status within simplex distributions to easyness of interpretation and good mathematical properties. In particular, we recall fundamental properties for the analysis of compositional data such as... more

The Dirichlet family owes its privileged status within simplex distributions to easyness of interpretation and good mathematical properties. In particular, we recall fundamental properties for the analysis of compositional data such as closure under amalgamation and subcomposition. From a probabilistic point of view, it is characterised (uniquely) by a variety of independence relationships which makes it indisputably the reference model for expressing the non trivial idea of substantial independence for compositions. Indeed, its well known inadequacy as a general model for compositional data stems from such an independence structure together with the poorness of its parametrisation. In this paper a new class of distributions (called Flexible Dirichlet) capable of handling various dependence structures and containing the Dirichlet as a special case is presented. The new model exhibits a considerably richer parametrisation which, for example, allows to model the means and (part of) th...

In this work a software architecture is presented for the automatic recognition of human arm poses. Our research has been carried on in the robotics framework. A mobile robot that has to find its path to the goal in a partially structured... more

In this work a software architecture is presented for the automatic recognition of human arm poses. Our research has been carried on in the robotics framework. A mobile robot that has to find its path to the goal in a partially structured environment can be trained by a human operator to follow particular routes in order to perform its task quickly. The system is able to recognize and classify some different poses of the operator's arms as direction commands like “turn-left”,“turn-right”,“go-straight”, and so on. A binary image of ...

Radar sensors, though successful in range parameters tracking, fall short in lateral characteristics tracking. On the other hand, vision systems carry out perfect estimation for lateral motion, but range parameters estimation does not... more

Radar sensors, though successful in range parameters tracking, fall short in lateral characteristics tracking. On the other hand, vision systems carry out perfect estimation for lateral motion, but range parameters estimation does not surpass the performance of radar. The exact estimation of vehicle's motion characteristics appears to be a crucial issue in modern automobile collision avoidance systems. Thus, a fusion

This paper investigates the ambiguities that exist in the bearing estimate of human footstep signals acquired using a single tri-axial geophone. Estimated angles for a series of footsteps from three different walking patterns are... more

This paper investigates the ambiguities that exist in the bearing estimate of human footstep signals acquired using a single tri-axial geophone. Estimated angles for a series of footsteps from three different walking patterns are evaluated. It is observed that there are two kinds of ambiguities, viz., energy and wave polarization. A systematic study of these ambiguities are presented using covariance