.... Memristor models Parasitic parameters Parameter estimation Memristor-based applications Memristors are predicted by Chua in 1971. In 2008 the first physical memristor, based on TiO₂ is created by Williams (Strukov et al., 2008). Memristors accumulate charges and have...

... Nell can be contacted at: martin.nell@iem.rwth-aachen.de 09 01 2018 18 02 2018 01 03 2018 © Emerald Publishing Limited 2018 Emerald Publishing Limited Licensed re-use rights only Particle swarm optimization Induction machine Parameter estimation Equivalent circuits...

... problems. Findings Unlike state estimation-based methods, the proposed method does not need the mathematical functions of measurements to simulation model parameters. The method can enhance other parameter estimation methods that are based on state estimation. Simulation results demonstrate the high...

... is defined in (4) from the quadratic mean of the temperature discrepancy: (Equation 4) (Equation 2) Multiobjective optimization Power transformers Finite element method Bushing Parameter estimation Temperature measurement In the design process of power transformers an important...

... X_n should minimize the mean‐square error ε _n of the approximation. Initial values of the parameters were determined from the linear model. © Emerald Group Publishing Limited 2013 Synchronous machine Magnetic co‐energy Mathematical modelling Parameter estimation...

... filtering is proposed for estimation of the hidden current from the noisy observations. Also, the problem of analyzing this model based on estimation of the unknown parameters is addressed from the likelihood‐based and Bayesian perspective. Findings Computational techniques for parameter estimation...

... Ferromagnetic materials Hysteresis Optimization Composites Parameter estimation With a soft magnetic composite material (SMC), it is possible to design new structures of transformers or inductances, for low frequency applications, which use the isotropic properties of these materials advantageously...