Communication systems are affected by channel distortions. Impulsive noise is one of the significant factors for impairments. The standard additive white Gaussian (AWGN) model and conventional estimation algorithms like least mean square (LMS) its variants tend to be ineffective under such conditions. This paper presents a robust adaptive algorithm using Geman-McClure estimator in diffusion-bas...

This paper presents a stable new algorithm for force/position control in robot manipulators. In this algorithm, position vectors are measured by sensors and then used in the control law. Since using force sensor has some issues such as high costs and technical problems, an approach is presented to overcome these issues. In this respect, force sensor is replaced by an adaptive fuzzy estimator to...

Development of an adaptive target state estimation algorithm for use with advanced missile guidance laws is presented. The target state estimator employs a linear neural network as the decisionmaking element in a nine-state dynamic model of the target. A Kalman filtering algorithm is used to estimate the neural network weights and the target states. The estimator performance is evaluated in a p...

It has recently been observed that, given the mean-variance relation, one can improve on the accuracy of the quasi-likelihood estimator by the adaptive estimator based on the estimation of the higher moments. The estimation of such moments is usually unstable, however, and consequently only for large samples does the improvement become evident. The author proposes a nonparametric estimating equ...

Consider a compound Poisson process which is discretely observed with sampling interval ∆ until exactly n nonzero increments are obtained. The jump density and the intensity of the Poisson process are unknown. In this paper, we build and study parametric estimators of appropriate functions of the intensity, and an adaptive nonparametric estimator of the jump size density. The latter estimation ...

We obtain a limit of a hierarchical Bayes estimator of a finite population mean when the sample size is large. The limit is in the sense of ordinary calculus, where the sample observations are treated as fixed quantities. Our result suggests a simple way to correct the hierarchical Bayes estimator to achieve design-consistency, a well-known property in the traditional randomization approach to ...