The premise of vehicle intelligent decision making is to obtain motion state parameters accurately and in real-time. Several cannot be measured directly by sensors, so estimation algorithms based on filtering are effective solutions. most representative algorithm the Kalman filter, especially standard unscented filter (UKF) that has been widely used because its superiority dealing with nonlinea...

Estimating the unknown parameter vector of system model is most important problems in identification. Especially cases where system's parameters are time-variable, it observed that estimations obtained using estimator have deviated from actual values, and therefore must be corrected to some extent. In this paper, methods for estimation a modelled with ARX Autoregressive Exogenous Input) conside...

Adaptive control as applied to machine tool systems refers to control of the operating parameters based on measurement of the process characteristics. Even the simplest adaptive control system with feedrate control based on cutting force measurements, is quite complex. The adaptive control loop is of a sampled-data nature with a nonlinear variable gain which depends on the operating parameters ...

Broadband signal transmission over frequencyselective fading channel often requires accurate channel state information at receiver. One of the most attracting adaptive channel estimation methods is least mean square (LMS) algorithm. However, LMS-based method is often degraded by random scaling of input training signal. To improve the estimation performance, in this paper we apply the standard l...

intermittent drying is a satisfactory technique for drying of heat sensitive grains especially rough rice. this method consists of two separate stages applied intermittently: drying and tempering. in this work, intermittent drying of rough rice is investigated both theoretically and experimentally. in order to characterize this process; a multi-scale model consisting of macroscopic and microsco...

In a convolution model, we observe random variables whose distribution is the convolution of some unknown density f and some known or partially known noise density g. We construct goodness-of-fit testing procedures, which are adaptive with respect to the smoothness parameter of unknown density f , and also (in some cases) to some unknown parameter of the noise density g. For known polynomially ...