Adaptive Estimation An adaptive estimator is an efficient estimator for a model that is only partially specified. For example, consider estimating a parameter that describes a sample of observations drawn from a distribution F . One natural question is: Is it possible that an estimator of the parameter constructed without knowledge of F could be as efficient (asymptotically) as any well-behaved...

In this paper a Fuzzy Tuned extended H∞ (FTH∞) estimator is designed and implemented in an Attitude Heading Reference System (AHRS), which is specialized to vehicular applications. In AHRS, 3axis accelerometers are allotted to measure the earth’s gravity field vector and then to update the roll and pitch angles obtained from gyros’ dynamic. Therefore, the AHRS on an accelerated vehicle will be ...

‎We extend the method of adaptive two-stage sequential sampling to‎‎include designs where there is more than one criteria is used in‎‎deciding on the allocation of additional sampling effort‎. ‎These‎‎criteria‎, ‎or conditions‎, ‎can be a measure of the target‎‎population‎, ‎or a measure of some related population‎. ‎We develop‎‎Murthy estimator for the design that is unbiased estimators for‎‎t...

The camera stabilizer stabilizes the camera’s line of sight by isolating the camera from the model uncertainties, disturbances of operating environment and system movements. This paper presents a voltage-base optimal adaptive fuzzy sliding mode control for camera stabilizer. In this proposed control method, a voltage-base sliding mode controller is applied. But unfortunately, undesirable ...

awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. therefore, the present study two hybrid models, wavelet- adaptive neural fuzzy interference system (wanfis) and wavelet- artificial neural network (wann) are used for flow prediction of gamasyab river (nahavand, hamedan, iran...

In order to reduce the …nite sample bias and improve the rate of convergence, local polynomial estimators have been introduced into the econometric literature to estimate the regression discontinuity model. In this paper, we show that, when the degree of smoothness is known, the local polynomial estimator achieves the optimal rate of convergence within the Hölder smoothness class. However, when...

A posteriori error estimation and related adaptive mesh-refining algorithms have themselves proven to be powerful tools in nowadays scientific computing. Contrary to adaptive finite element methods, convergence of adaptive boundary element schemes is, however, widely open. We propose a relaxed notion of convergence of adaptive boundary element schemes. Instead of asking for convergence of the e...

Recent developments in Soft computing techniques, power electronic switches and low-cost computational hardware have made it possible to design and implement sophisticated control strategies for sensorless speed control of AC motor drives. Such an attempt has been made in this work, for Sensorless Speed Control of Induction Motor (IM) by means of Direct Torque Fuzzy Control (DTFC), PI-type fuzz...

This paper presents the design and implementation of an adaptive fuzzy logic controller for the speed control of brushless dc motors. The proposed system uses an adaptation of the slope of the membership functions of the variables used in the conventional fuzzy controller based on the magnitude of the error. A simulation analysis of the fuzzy controller and the adaptive fuzzy controller are don...

An incremental, nonparametric probability estimation procedure using a variation of the Fuzzy ARTMAP (FAM) neural network is introduced. The resulted network, called Fuzzy ARTMAP with Relevance factor (FAMR), uses a relevance factor assigned to each sample pair, proportional to the importance of that pair during the learning phase. We prove that our probability estimator is correct. The FAMR ca...