Time of arrival (TOA) estimation in multipath dense environment for UWB backscattering radio frequency identification (RFID) system is challenging due to the presence of strong clutter. In addition, the backscattering RFID system has peculiar signal transmission and modulation characteristics, which are considerably different from conventional communication and localization systems. The existin...

This work presents a novel approach for the accurate estimation of multiple time-delays from frequency response distributed system. The proposed is based on powerful and flexible machine learning technique, namely, least-square support vector (LS-SVM). LS-SVM regression used to construct metamodel transfer function describing generic linear time-invariant system in delayed-rational form. Specif...

Channel estimation in conjunction with impulsive noise (IN) mitigation using compressive sensing is proposed for OFDM based power line communication (PLC) systems. Compressive sensing (CS) based IN mitigation algorithms use silent-pilots (or zero-subcarriers) to estimate and cancel the IN at receiver. To estimate the channel and IN jointly, non-zero pilots have to be used. However, the usage of...

This paper proves the effectiveness of Least Mean Square (LMS) estimation algorithm for estimation of power system harmonics, inter-harmonics and sub-harmonics of distorted signal. Accurate estimation can be achieved by this technique for harmonics, sub-harmonics and inter-harmonics estimation including possible variation in the signal such as change in amplitude when applied to a distorted pow...

This paper presents a novel algorithm for least squares (LS) estimation of both stationary and nonstationary signals which arise from Volterra models. The algorithm concerns the recursive implementations of the method of LS which usually have a weighting factor in the cost function. This weighting factor enables nonstationary signal models to be tracked. In particular, the behavior of the weigh...

Halftoning is the core algorithm governing most digital printing or imaging devices, by which images of continuous tones are converted to ensembles of discrete or quantum dots. It is through the human vision system (HVS) that such fields of quantum dots can be perceived almost identical to the original continuous images. In the current work, we propose a least-square based halftoning model with...

We consider the channel estimation for two-way relay OFDM networks. We proposed an LS-based channel estimation algorithm under block-based training schemes. Based on the mean square error (MSE) criterion, the condition and the design method for optimal training sequences are discussed. To reduce peak-to-average power ratio (PAPR), a special sequence called Zadoff-Chu sequence is employed to des...

This paper presents a new approach called clustering technique-based least square support vector machine (CT-LS-SVM) for the classification of EEG signals. Decision making is performed in two stages. In the first stage, clustering technique (CT) has been used to extract representative features of EEG data. In the second stage, least square support vector machine (LS-SVM) is applied to the extra...

The least squares (LS) can be used for nonlinear autoregressive (NAR) and nonlinear autoregressive moving average (NARMA) parameter estimation. However, for nonlinear cases, the LS results in biased parameter estimation due to its assumption that the independent variables are noise free. The total least squares (TLS) is another method that can used for nonlinear parameter estimation to increase...