In this paper, we establish a unified framework for subspace identification (SID) of linear parameter-varying (LPV) systems to estimate LPV state–space (SS) models in innovation form. This enables us derive novel SID schemes that are extensions existing time-invariant (LTI) methods. More specifically, the open-loop, closed-loop, and predictor-based data-equations (input–output surrogate forms S...

the purpose of the present study is to compare the changes in b-value parameter using frequency-magnitude distribution for the data before and after the silakhor earthquake by gutenberg-richter relation. the variations of b-values are investigated using broadband iranian national seismic network center (bin). besides, spatial and time variations of the parameters were analyzed. the spatial vari...

Fuzzy modeling generally comprises structure identification and parameter identification. The former determines the structure of a rule-base, whereas the latter determines the contents of each rule. Applying neural networks or genetic algorithms to identify the parameter sets and structures of a fuzzy system is increasingly popular owing to their ability to learn and adapt. However, most conven...

Accurate knowledge of transmission line (TL) impedance parameters helps to improve accuracy in relay settings and power flow modeling. To improve TL parameter estimates, various algorithms have been proposed in the past to identify TL parameters based on measurements from Phasor Measurement Units (PMU’s). These methods are based on the positive sequence TL models and can generate accurate posit...