A new robust and computationally efficient solution to least-squares problem in the presence of round-off errors is proposed. The properties of a harmonic regressor are utilized for design of new combined algorithms of direct calculation of the parameter vector. In addition, an explicit transient bound for estimation error is derived for classical recursive least-squares algorithm using the Lya...

A new receiver structure able to deliver high data rates in a multiple-input multiple-output (MIMO) frequency selective wireless environment is proposed and investigated in this paper. The optimal solution for the finite length MIMO decision feedback equalizer (DFE) with cancellation is derived and used to illustrate the potential of this architecture for space-time communications. LMS and RLS ...

A reduced-rank framework with set-membership filtering (SMF) techniques is presented for adaptive beamforming problems encountered in radar systems. We develop and analyze stochastic gradient (SG) and recursive least squares (RLS)-type adaptive algorithms, which achieve an enhanced convergence and tracking performance with low computational cost as compared to existing techniques. Simulations s...

In the previous paper (Pupeikis, 2000) the problem of closed-loop robust identification using the direct approach in the presence of outliers in observations have been considered. The aim of the given paper is a development of the indirect approach used for the estimation of parameters of a closed-loop discrete-time dynamic system in the case of additive correlated noise with outliers contamina...

This paper studies a fault tolerant control strategy for a four wheel skid steering mobile robot (SSMR). Through this work the fault diagnosis procedure is accomplished using structural analysis technique while fault accommodation is based on a Recursive Least Squares (RLS) approximation. The goal is to detect faults as early as possible and recalculate command inputs in order to achieve fault ...

In adaptive signal processing the principle of exponentially weighted recursive least-squares plays a major role in developing various estimation algorithms. It is based on the concept of discounting of old measurements and allows for better performance in problems with time-varying signals and signals in nonstationary noise. In this paper we show how this concept can be combined with the Bayes...

Recent studies have demonstrated that correntropy is an efficient tool for analyzing higher-order statistical moments in nonGaussian noise environments. Although correntropy has been used with complex data, no theoretical study was pursued to elucidate its properties, nor how to best use it for optimization . This paper presents a probabilistic interpretation for correntropy using complex-value...

In this work, we propose a low-complexity variable forgetting factor (VFF) mechanism for recursive least square (RLS) algorithms in interference suppression applications. The proposed VFF mechanism employs an updated component related to the time average of the error correlation to automatically adjust the forgetting factor in order to ensure fast convergence and good tracking of the interferen...