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Indoor positioning using weighted magnetic field signal distance similarity measure and fuzzy based algorithms
Published 2021“…The lowest average Euclidean distance is chosen, and the average estimated location of the RPs is calculated. Lastly, for the fuzzy algorithm, a rule-based decision is applied to select whether the triangle area or average Euclidean algorithm is used to find the final estimated position. …”
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Reduced-rank technique for joint channel estimation in TD-SCDMA systems.
Published 2013“…Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems
Published 2013“…Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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Orthogonal least square algorithm and its application for modelling suspension system
Published 2001“…Orthogonal least square estimation is an algorithm which can determine the structure of a model by identifying the significant terms contributed to the model and also capable of providing the final values of parameter estimates. …”
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Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems
Published 2012“…Equations for reduced rank-joint channel estimation (JCE) are derived and compared against traditional full rank-joint channel estimators: least square (LS) or Steiner, enhanced LS, and minimum mean square error algorithms. …”
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PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…Typically, parameter estimation is performed using various types of Least Squares (LS) algorithms due to its stable and efficient numerical computation. …”
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State estimation of the power system using robust estimator
Published 2016“…In this study, a new robust algorithm based on the quasi weighted least squares (QWLS) estimator is presented. …”
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Conference or Workshop Item -
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Model selection approaches of water quality index data
Published 2016“…In order to select the best model, it is vital to ensure that proper estimation method is chosen in the modelling process.Different estimators have been proposed for the estimation of parameters of a model, including the least square and iterative estimators.This study aims to evaluate the forecasting performances of two algorithms on water quality index (WQI) of a river in Malaysia based on root mean square error (RMSE) and geometric root mean square error (GRMSE).Feasible generalised least squares (FGLS) and iterative maximum likelihood (ML) estimation methods are used in the algorithms, respectively.The results showed that SUREMLE-Autometrics has surpassed SURE-Autometrics; another simultaneous selection procedure of multipleequation models.Two individual selections, namely Autometrics-SUREMLE and Autometrics-SURE, though showed consistency only for GRMSE.All in all, ML estimation is a more appropriate method to be employed in this seemingly unrelated regression equations (SURE) model selection.…”
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ADAPTIVE LINEAR ALGORITHMS FOR POWER SYSTEM FUNDAMENTAL AND HARMONIC ESTIMATION
Published 2015“…Hence, one of the objectives of this thesis is to address and enhance the introduced fundamental frequency adaptive filter method which was based on modified variable step size LMS (MVSS) algorithm using generalized square error normalized LMS algorithm. …”
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11
Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…They used the classical bootstrap method to estimate the bootstrap location and the scale parameters based on calculating the Mean of Squared Residual (MSR). …”
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MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD
Published 2017“…In this research. novel algorithms have been developed to: (I) isolate the less interacting channe Is using a modified partial correlation algorithm. (2) achieve unbiased and consistent parameter estimates using an iterative LLMS algorithm and (3) develop parsimonious models for closed-loop MIMO systems. …”
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14
Performance of MIMO space-time coded system and training based channel estimation for MIMO-OFDM system
Published 2006“…Firstly it has investigated the performance of MIMO-STBC system and surveyed the effect of imperfect channel estimation on performance of MIMO-OFDM system. Secondly, it has focused on training based channel estimation algorithm for MIMO-OFDM system. …”
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15
RSA Encryption & Decryption using JAVA
Published 2006“…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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Final Year Project -
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MIMO OFDM channel estimation based on RLS algorithm: the time- versus frequency-domain implementations
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A new robust computational approach for the electric power system parameters
Published 2017“…This paper, presents a new robust algorithm for power system SE environments. The proposed approach not only has the comparative performance of the conventional loss function based on the estimator of the WLS additionally, it also considers loss function based on the quasi weighted least squares (QWLS) estimator. …”
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Optimal neural network approach for estimating state of energy of lithium-ion battery using heuristic optimization techniques
Published 2023Conference Paper -
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Multiple equations model selection algorithm with iterative estimation method
Published 2016“…There have been various procedures suggested to date, whether through manual or automated selections, to choose the best model.This study nonetheless focuses on an automated selection for multiple equations model with the use of iterative estimation method. In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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