In this paper we present error analysis for a Monte Carlo algorithm for evaluating bilinear forms of matrix powers. An almost Optimal Monte Carlo (MAO) algorithm for solving this problem is formulated. Results for the structure of the probability error are presented and the construction of robust and interpolation Monte Carlo algorithms are discussed. Results are presented comparing the perform...

We present a new localization algorithm called Sensor Resetting Localization which is an extension of Monte Carlo Localization. The algorithm adds sensor based resampling to Monte Carlo Localization when the robot is lost. The new algorithm is robust to modelling errors including unmodelled movements and systematic errors. The algorithm can be used in real time on systems with limited computati...

in this paper, multi-microgrids (mmg) are considered as future smart distribution grids, in which small scale energy resources (sser) are main power generation units with small scales. optimal operation of microgrids in defined intervals is carried out to achieve economic conditions in distribution systems. the defined operating problem is optimized using a heuristic algorithm considering uncer...

background: inclusion of inhomogeneity corrections in intensity modulated small fields always makes conformal irradiation of lung tumor very complicated in accurate dose delivery. objective: in the present study, the performance of five algorithms via monte carlo, pencil beam, convolution, fast superposition and superposition were evaluated in lung cancer intensity modulated radiotherapy planni...

in recent years, some statisticians have studied the signal detection problem by using the random field theory. in this paper we have considered point estimation of the gaussian scale space random field parameters in the bayesian approach. since the posterior distribution for the parameters of interest dose not have a closed form, we introduce the markov chain monte carlo (mcmc) algorithm to ap...