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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 proposes a novel Iterative Learning Control (ILC) framework for spatial tracking. Spatial tracking means that the temporal component is not fixed which violates the standing assumption on time intervals in traditional ILC. The proposed framework allows for the length of the time interval to change with each iteration. To relate the spatial information from the past to the present iteration,...
Bat algorithm is a novel swarm intelligent algorithm inspired by the echolocation behavior of bats. However, the exploitation capability is not well for some multi-model problems. In this paper, a new parameter, inertia weight is introduced to improve the local search capability. In this new variant, the inertia weight is used to control the influence of the inertia of previous velocity for each bat...
as part of the EVEREST project of ESA, we implemented in CST Particle Studio™ models of different microwave samples for L- and Ku- bands to investigate the Multipactor effect in the presence of the fringing fields. Using a diversity of Secondary Electron Yield (SEY) data provided from different measurement facilities along with the available ECSS standards, cross validation is examined between the...
Three applications in wireless networks where model-free stochastic learning is applicable, are discussed. The learning based optimization problems are formulated and simulation results are presented. Some open issues are also discussed.
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