The statistical matching problem involves the integration of multiple datasets where some variables are not observed jointly. This missing data pattern leaves most statistical models unidentifiable. Statistical inference is still possible when operating under the framework of partially identified models, where the goal is to bound the parameters rather than to estimate them precisely. In many m...

We introduce three novel semi-parametric extensions of probabilistic canonical correlation analysis with identifiability guarantees. We consider moment matching techniques for estimation in these models. For that, by drawing explicit links between the new models and a discrete version of independent component analysis (DICA), we first extend the DICA cumulant tensors to the new discrete version...

Mean value and cross-covariance function of chaotic binary sequences are evaluated for chaotic maps with specific properties. We also take into account the effect of fixedand floating-point representations on statistical properties of chaotic generators. Thus, one is able to obtain possible candidates for pseudo-random binary sequences generation. Results of statistical tests applied to chaotic...

Introduction Conclusions References Tables Figures

ontology is the main infrastructure of the semantic web which provides facilities for integration, searching and sharing of information on the web. development of ontologies as the basis of semantic web and their heterogeneities have led to the existence of ontology matching. by emerging large-scale ontologies in real domain, the ontology matching systems faced with some problem like memory con...

The role of associativity or WDVV equations in effective supersymmetric quantum theories is discussed and it is demonstrated that for wide class of their solutions when residue formulas are valid the proof of associativity equations can be reduced to solving the system of ordinary linear equations and depends only upon corresponding matching and nondegeneracy conditions. The covariance of WDVV ...

In multisensor target tracking, each sensor can have its own target state estimate based on the local sensor measurements. Most existing communication networks between local trackers/sensors transmit to a fusion center the local track estimates–sometimes without any estimation error covariances, sometimes with partial covariance information and only rarely with full covariance information. In o...

A transfer alignment is used to initialize, align, and calibrate a SINS(Slave INS) using MINS(Master in motion. This paper presents an airborne with velocity azimuth matching estimate inertial sensor biases under the wing flexure influence. study also considers lever arm, time delay relative orientation between MINS SINS. The traditional only uses matching. In contrast, this utilizes prevent di...

We describe a new region descriptor and apply it to two problems, object detection and texture classification. The covariance of d-features, e.g., the three-dimensional color vector, the norm of first and second derivatives of intensity with respect to x and y, etc., characterizes a region of interest. We describe a fast method for computation of covariances based on integral images. The idea p...

Conventional algorithms used for parameter estimation in colocated multiple-input-multiple-output (MIMO) radars require the inversion of the covariance matrix of the received spatial samples. In these algorithms, the number of received snapshots should be at least equal to the size of the covariance matrix. For large size MIMO antenna arrays, the inversion of the covariance matrix becomes compu...