We obtain upper and lower bounds for the H" norm of the RLS (Recursive-Least-Squares) algorithm. The H" norm may be regarded aa the worst-case energy gain from the disturbances to the prediction errors, and is therefore a measure of the robustness of an algorithm to perturbations and model uncertainty. Our results allow one to compare the robustness of RLS compared to the LMS (Least-Mean-Square...

Abstract In order to reduce the bit error rate and improve anti-interference performance, this paper proposes a channel estimation algorithm based on RLS. RLS obtains current data by modifying final data. First, first is estimated least squares (LS), then date adjusted in real time through forgetting factor recursive formula obtain all The results show that can computation, accuracy of estimati...

A bank of recursive least-squares (RLS) estimators is proposed for the estimation of the uncertainty intervals of the parameters of an equation error model (or RLS model) where the equation error is assumed to lie between known upper and lower bounds. It is shown that the off-line least-squares method gives the maximum and minimum parameter values that could have produced the recorded input-out...

Background There has been a recent interest in adaptive algorithms to handle sparsity in various signals and systems (Gu et al. 2009; Chen et al. 2009; Babadi et al. 2010; Angelosante et al. 2010; Eksioglu 2011; Eksioglu and Tanc 2011; Kalouptsidis et al. 2011). The idea is to exploit a priori knowledge about sparsity in a signal that needs to be processed for system identification. Several alg...

The implementation of each function a battery management system (BMS) depends on sensor data. Efficient fault diagnosis is essential to the durability and safety systems. In this paper, model-based scheme fault-tolerant control strategy for voltage current are proposed with recursive least-square (RLS) unscented Kalman filter (UKF) algorithms. uses an open-circuit residual generator capacity ge...

Full-duplex unmanned aerial vehicle (UAV) communication systems are characterized by mobility, so the self-interference (SI) channel characteristics change over time constantly. In full-duplex UAV systems, difficulty is to eliminate SI in time-varying channels. this paper, we propose a pilot-aid digital cancellation (SIC) method. First, pilot inserted into data sequence uniformly, and modeled a...

Recursive (online) expectation–maximization (EM) algorithm along with stochastic approximation is employed in this paper to estimate unknown time-invariant/variant parameters. The impulse response of a linear system (channel) is modeled as an unknown deterministic vector/process and as a Gaussian vector/process with unknown stochastic characteristics. Using these models which are embedded in wh...

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...

In the previous papers (Novovicova, 1987; Pupeikis 1991) the problem of recursive least square (RLS) estimation of dynamic systems parameters in the presence of outliers in observations has been considered, when the filter, generating an additive noise, has a transfer function of a particular form, see Fig. 1, 2. The aim of the given paper is the development of well-known classical techniques f...

The Recursive Least Squares (RLS) algorithm is renowned for its rapid convergence but in some scenarios it fails to show swiftness required by several applications. Such failure may result due to different limiting conditions. Gain vector plays an essential role in the performance of RLS algorithm. This paper proposes a modification in Gain vector that results in RLS algorithm performing much b...