Search Results - (( data selection method algorithm ) OR ( rate estimation method algorithm ))

Sure (EM)-Autometrics: An Automated Model Selection Procedure with Expectation Maximization Algorithm Estimation Method (S/O 14925) by Kamarudin, Nur Azulia

“…Hence, this study concentrates on an automated model selection procedure for the SURE model by integrating the expectation-maximization (EM) algorithm estimation method, named SURE(EM)-Autometrics. …”
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Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

“…The empirical results for both algorithms performed well as compared to other models selection procedures, particularly using WQI data where the sample size is bigger and has good quality data. …”
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On iterative low-complexity algorithm for optimal antenna selection and joint transmit power allocation under impact pilot contamination in downlink 5g massive MIMO systems by Mohammed Ahmed, Adeeb Ali

“…Massive MIMO systems are affected by pilot contamination, which influences the data rate of the system. In this thesis, highly interfering UEs in adjacent cells were identified based on estimates of large-scale fading and then included in the joint channel processing to achieve the desired tradeoff between the effectiveness and the efficiency of channel estimation in order to increase the data rate. …”
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Reconstruction Algorithm In Ofdm System by Hwong, Sing Pui

“…Conventional channel estimation (CE) methods had been introduced to estimate CSI, but they are not able to exploit the wireless channel sparsity which causes reduction in bandwidth efficiency. …”
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Evaluating A New Adaptive Group Lasso Imputation Technique For Handling Missing Values In Compositional Data by Tian, Ying

“…The complexity of compositional data with missing values renders traditional estimation methods inadequate. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

“…Secondly, the modeling method of the proposed PV module is validated by experimental data. …”
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Fluorescence decay analysis using expotential compensation deconvolution by Salami, Momoh Jimoh Eyiomika, Khalifa, Othman Omran, Jibia, Abdussamad Umar

“…Eigenvector algorithms are then used to further model the resulting complex exponentials to obtain better estimates of decay rates and number of components. …”
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Subspace Techniques for Brain Signal Enhancement by Kamel , Nidal, Yusoff, Mohd Zuki

“…Both the simulation and real human data show that the subspace methods generate reasonably low errors and high success rate. …”
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Enhancing the QoS performance for mobile station over LTE and WiMAX networks / Mhd Nour Hindia by Hindia, Mhd Nour

“…Then, a multi criteria with two-threshold algorithm is proposed to prioritize the selection between the LTE and WiMAX as target technologies. …”
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A comparative study and simulation of object tracking algorithms by Ji, Yuanfa, Yin, Pan, Sun, Xiyan, Kamarul Hawari, Ghazali, Guo, Ning

“…The experiment mainly analyzes the results through three indicators of accuracy, success rate, and tracking speed of various algorithms, and draws the following conclusions: Compared with traditional algorithms, the tracking speed of correlation filtering algorithms can reach more than 100 frames per second, while the precision of deep learning methods can reach more than 0.7. …”
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Analysis of transient multiexponential signals using exponential compensation deconvolution by Jibia, Abdussamad Umar, Salami, Momoh Jimoh Eyiomika

“…In the third step, eigenvector algorithms are used to process the resulting complex exponentials to obtain better estimates of decay rates and number of components. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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Modelling and Forecasting the Kuala Lumpur Composite Index Rate of Returns Using Generalised Autoregressive Conditional Heteroscedasticity Models by Abdul Muthalib, Maiyastri

“…Methods for correcting the outliers and splitting the heterogeneous data are proposed. …”
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Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture by Chong, Jin Hui

“…It is shown that the computational complexity of proposed FAST-QR detection algorithm is approximately 48 % lower than the conventional QR decomposition detection algorithm. …”
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Application of Decision Tree Algorithm for Predicting Monthly Pan Evaporation Rate by Abed M., Imteaz M.A., Ahmed A.N., Huang Y.F.

Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms by Abed M., Imteaz M.A., Ahmed A.N., Huang Y.F.

Channel Modelling and Estimation in Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing Wireless Communication Systems by Hezam, Mohammed Abdo Saeed

“…The second issue addressed in this thesis is the channel estimation in MIMO OFDM systems. New time-domain (TD) adaptive estimation methods based on recursive least squares (RLS) and normalized least-mean squares (NLMS) algorithms are proposed. …”
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Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment by Sojodishijani, Omid

“…From a dimensionality reduction evaluation aspect, the average misclassification error of the proposed method in low-rank feature space is 9.6% and same error rate for three other well-known feature extraction methods is 21.21%. …”
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UV-vis spectrophotometric and artificial neural network for estimation of ammonia in aqueous environment using cobalt(ii) ions by Ling Ling T., Ahmad M., Yook Heng L.

UV-vis spectrophotometric and artificial neural network for estimation of ammonia in aqueous environment using cobalt(II) ions by Ling, TL, Ahmad, M, Heng, LY

“…The interference effect was found to be negligible for a number of foreign ions present in the reaction medium during NH3 determination in an aqueous environment. A set of absorbance data for the [Co(NH3)(6)](2+) complex at selected wavelengths was input for ANN training using a back-propagation algorithm. …”