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This paper presents the application of runs test for indirect consideration of observation's autocorrelation in estimation of a standard uncertainty of arithmetic mean value. At first stage researches were performed by Monte Carlo (MC) simulation for two kind's random signals: first order autoregression (AR) and moving averaging (MA). Comparison of theoretical values of effective number of observations...
This paper considers the problem of decentralized, cooperative, and dynamic self-localization in wireless sensor networks. In particular, we are interested in a restrictive but very realistic scenario where few anchors are deployed and each anchor whose location is priori known may only communicate with very few agents (e.g. just one agent) whose location is unknown and to-be-estimated. The lack of...
This paper compares the stochastic convergence of the Uniform Random number generators of two simulation software namely Matlab and Python and establishes the significance in choosing the right random number generator for error propagation studies. It further discusses about the application of Gaussian type of these random number generators to nonlinear cases of Error propagation using the Monte Carlo...
The multilevel Monte Carlo method is applied to an academic example in the field of electromagnetism. The method exhibits a reduced variance by assigning the samples to multiple models with a varying spatial resolution. For the given example it is found that the main costs of the method are spent on the coarsest level.
In clinical neuroimaging applications where subjects belong to one of multiple classes of disease states and multiple imaging sources are available, the aim is to achieve accurate classification while assessing the importance of the sources in the classification task. This work proposes the use of fully Bayesian multiple-class multiple-kernel learning based on Gaussian Processes, as it offers flexible...
The resolution of complex design problems requires a distributed design system that considers the involvement of various designers. Inconsistencies of design objectives and working procedures of distributed subsystems can cause design conflicts due to couplings among their subproblems. Another issue is the management of imprecision in design systems caused by the lack of knowledge about the final...
A previous paper (Spall, 2010) described a method for estimating the reliability of a complex system based on a combination of full system and subsystem tests. A maximum likelihood estimate (MLE) is formed to estimate the subsystem reliabilities and the full system reliability. While the previous paper gave conditions under which the MLE converges to the true reliability as the sample size gets large,...
The objective of this work is to present a new approach to the random modeling of complex systems in ElectoMagnetic Compatibility (EMC). This contribution aims to compute high orders statistics and study the impact of parameter uncertainties on various EMC topics including transmission lines, radiation and immunity problems. The agreement between results from the Stochastic Collocation (SC) method...
Entropy analysis is a key factor for ensuring the accuracy of measured data in pump test. But a unified and widely accepted evaluation method has not been formed. In this paper, an improved method based on the combination of maximum entropy and Monte Carlo method is proposed. Based on maximum entropy concept, statistical model of random distribution variables was presented, and a parameter estimation...
The ability of mobile robots to quickly and accurately analyze their dynamics is critical to their safety and efficient operation. In field conditions, significant uncertainty is associated with terrain and/or vehicle parameter estimates, and this must be considered in an analysis of robot motion. Here a Multi-Element generalized Polynomial Chaos (MEgPC) approach is presented that explicitly considers...
The main contribution of this paper is an analysis of the FastSLAM algorithm for simultaneous localization and mapping (SLAM) problem. The convergence properties of the landmark uncertainty for FastSLAM are provided. The proofs clearly show that the limit of the uncertainty for the landmark estimation has no relationship with the vehicle's initial pose uncertainty. Furthermore, the consistency of...
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