This paper proposes the online sequential extreme learning machine algorithm based on the recursive partial leastsquares method (OS-ELM-RPLS). It is an improvement to the online sequential extreme learning machine based on recursive least-squares (OS-ELM-RLS) introduced in [1]. Like in the batch extreme learning machine (ELM), in OSELM-RLS the input weights of a single-hidden layer feedforward ...

Transversal Recursive Least Squares (RLS) algorithms estimate filter coefficients which minimize the accumulated sum of the square of the error residuals termed the error power. In this paper the sensitivity of this error power to random perturbations about the optimum filter coefficients is investigated. Expressions are derived for the mean and variance of the deviation from the optimum error ...

In this correspondence, a new time and order recursive method for on-line tracking of system order and parameters using recursive least squares (RLS) is presented. The method consists of two parts: a time updating portion that uses existing RLS inverse QR decomposition algorithms and a new computationally efficient “order downdating” portion that calculates the model parameters and residual err...

The electrocardiogram (ECG) is used for diagnosis of heart diseases. In a few circumstances the recorded ECG signals are corrupted by various noise signals caused by power line interference, base line wander, electrode movement, muscular movement (EMG) etc. These noise signals are known as artifacts. These artifacts mislead the diagnosis of heart which is not desired. To avoid this problem caus...

In this paper, we study the problem of beam tracking a multipath channel in millimeter-wave massive MIMO communication system using adaptive filters. We focus on performance least-mean-square filter (LMS) and recursive least-squares (RLS) algorithms, compared to reference extended Kalman (EKF), scenarios where wireless is dominated by single line sight (LOS) path or small number strong paths. T...

120  ABSTRACT One of the main problem in biomedical data processing like electrocardiography is the separation of the wanted signal from noises caused by power line interference, external electromagnetic fields, random body movements and respiration. Different types of digital filters are used to remove signal components from unwanted frequency ranges. It is difficult to apply filters with fix...

Total least squares parameter estimation is an alternative to least squares estimation though much less used in practice, partly due to the absence of eecient recursive algorithms or parallel architectures. Here it is shown how previously developed systolic algorithms/architectures for recursive least squares estimation can be used for recursive total least squares problems. Unconstrained as we...

The goal of this paper is to perform a performance analysis for speech enhancement using classical adaptive filters with kalman filter. In many applications like speech recognition, hearing aids, forensic applications and telephone conversations etc... As the enhancement of speech signals is of very important. The performance of the speech recognition system is also reduces if the speech signal...

A digital-assisted photonic analog wideband radio-frequency multipath self-interference cancellation (SIC) and frequency downconversion method based on a dual-drive Mach–Zehnder modulator the recursive least square (RLS) algorithm is proposed demonstrated for in-band full-duplex systems. Besides reference direct-path (SI) signal, RLS used to construct another residual SI signal from direct path...

For the lifted input–output representation of general dual-rate sampled-data systems, this paper presents a decomposition based recursive least squares (D-LS) identification algorithm using the hierarchical identification principle. Compared with the recursive least squares (RLS) algorithm, the proposed D-LS algorithmdoes not require computing the covariancematriceswith large sizes andmatrix in...