Search Results - (( data estimation techniques algorithm ) OR ( java application tree algorithm ))
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The findings of this research provide two new iterative algorithms for estimating the parameters of the AFT model with interval-censored data, and also two new resampling techniques for estimating the covariance matrix of estimators. …”
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Thesis -
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Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems
Published 2013“…The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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Article -
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Reduced Rank Technique for Joint Channel Estimation and Joint Data Detection in TD-SCDMA Systems
Published 2012“…The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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Analysis of multiexponential transient signals using interpolation-based deconvolution and parametric modeling techniques
Published 2003“…Direct deconvolution approach often leads to poor resolution of ihe estimated decay rates since the fast Fourier transform (FFT) algorithm is used to analyze the resulting deconvolved data. …”
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Proceeding Paper -
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Reduced-rank technique for joint channel estimation in TD-SCDMA systems.
Published 2013“…The adopted reduced rank technique is based on singular value decomposition algorithm. …”
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Pose estimation algorithm for mobile Augmented Reality based on inertial sensor fusion
Published 2021“…Furthermore, gyroscope sensor data is incorporated with the vision-based pose estimation. …”
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Non pilot and pilot aided least square channel estimation algorithm in MIMO-OFDM system / Nursarah Ainaa Abdul Halim
Published 2013“…This project is about analyze and implement channel estimation techniques for MIMO-OFDM Systems with Least Squares (LS) Algorithm channel estimation by comparing non pilot and pilot aided result and the result is supposed the Pilot aided will have a better performance.…”
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Thesis -
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Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…Unfortunately, many statistics practitioners are not aware of the fact that most of the classical bootstrap techniques are based on the OLS estimates which is sensitive to outliers. …”
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The comparison study among optimization techniques in optimizing a distribution system state estimation
Published 2017“…The states of these systems are first estimated through centralized approach using the proposed algorithm to compare with weighted least squares technique. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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The development of parameter estimation method for Chinese hamster ovary model using black widow optimization algorithm
Published 2020“…Metaheuristic parameter estimation is an algorithm framework that is processed using some technique to generate a pattern or graph. …”
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Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm
Published 2015“…The next stage is to approximate the parameters of the model and finally, the mathematical model is validated. In this paper, a technique termed as Simultaneous Model Order and Parameter Estimation (SMOPE), which is specifically based on Gravitational Search Algorithm (GSA) is proposed to combine model order selection and parameter estimation in one process. …”
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Conference or Workshop Item -
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Performance of MIMO space-time coded system and training based channel estimation for MIMO-OFDM system
Published 2006“…It should be mentioned that reduction of computational complexity of the channel estimation and data detection algorithm is a major challenge for receiver design in MIMO-OFDM system, and complication of receiver design is mostly due to these algorithms. …”
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Thesis -
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Algorithm optimization and low cost bit-serial architecture design for integer-pixel and sub-pixel motion estimation in H.264/AVC / Mohammad Reza Hosseiny Fatemi
Published 2012“…This thesis is concerned with algorithm optimization and efficient low cost architecture design for integer motion estimation (IME) and sub-pixel motion estimation (SME) of H.264/AVC. …”
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Thesis -
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Power System State Estimation In Large-Scale Networks
Published 2010“…This thesis describes a pre-screening process to identify the bad measurements and the measurement weights before performing the WLS estimation technique employed in SE. The autoregressive (AR) techniques. …”
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Thesis -
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA
Published 2012“…The proposed data store management technique is combined with the central finite difference based gradient estimate to generate a model robust against both correlated data and irregular sampled data. …”
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Parameter estimation of multicomponent transient signals using deconvolution and ARMA modelling techniques
Published 2003“…An improved method that is based of the combination of Gardner transformation, optimal compensation deconvolution, and signal modelling techniques is suggested in this paper. In this method of analysis the exponential signal is converted to a convolution model whose input is a train of weighted delta function that contains the signal parameters to be determined.The resolution of the estimated decay rates is poor if the conventional fast Fourier transform (FFT) algorithm is used to analyse the resulting deconvolved data. …”
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Parameter estimation in double exponential smoothing using genetic algorithm / Foo Fong Yeng, Lau Gee Choon and Zuhaimy Ismail
Published 2014“…The objective of this research is to estimate the Double Exponential Smoothing by using Genetic Algorithm Mechanism. …”
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Research Reports -
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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…Accuracy by using 80:20 ratio of training and test data gives result 98% of accurate training data, and 73% of test data are predicted with the proposed algorithm while 91 and 40% of the DNN models are predicted in training and test data.…”
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Conference or Workshop Item
