Search Results - (( simulation estimation method algorithm ) OR ( based application method algorithm ))
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1
Adaptive beamforming algorithm based on Simulated Kalman Filter
Published 2017“…Zakwan, applies Opposition-Based Learning method to improve the exploration capabilities of SKF algorithm. …”
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Thesis -
2
Parameter estimation and outlier detection in linear functional relationship model / Adilah Abdul Ghapor
Published 2017“…The applicability of all the proposed methods is illustrated in real life examples.…”
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Thesis -
3
New Fast Block Matching Algorithm Using New Hybrid Search Pattern And Strategy To Improve Motion Estimation Process In Video Coding Technique
Published 2016“…These 6 algorithms are divided into 3 main methods namely Method A, Method B, and Method C depending on their search patterns and strategies. …”
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4
Multiple equations model selection algorithm with iterative estimation method
Published 2016“…This estimation method is equivalent to maximum likelihood estimation at convergence. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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6
Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…These algorithms are inspired by the estimation capability of the well-known Kalman filter estimation method. …”
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7
Opposition- based simulated kalman filters and their application in system identification
Published 2017“…Among the various kinds of optimization algorithms, Simulated Kalman Filter (SKF) is a new population-based optimization algorithm inspired by the estimation capability of Kalman Filter. …”
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8
The compact genetic algorithm for likelihood estimator of first order moving average model
Published 2012“…Simulation results based on MSE were compared with those obtained from the moments method and showed that the Canonical GA and compact GA can give good estimator of θ for the MA(1) model. …”
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Conference or Workshop Item -
9
Dynamic robust bootstrap method based on LTS estimators
Published 2009“…We call this method Dynamic Robust Bootstrap-LTS based (DRBLTS) because here we have employed the LTS estimator in the modified bootstrap algorithm. …”
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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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12
Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…The Ordinary Least Squares (OLS) method is often used to estimate the parameters of a linear model. …”
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13
Neighbour-based on-demand routing algorithms for mobile ad hoc networks
Published 2017“…All the three proposed algorithms are evaluated using discrete event simulation, in particular Network Simulator tool (NS2), and compared with the latest routing algorithm (NCPR ) and fundamental algorithm (AODV) using five performance metrics. …”
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14
APPLICATION OF BURG’S ALGORITHM IN STATE ESTIMATION
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Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…Besides, algorithm based method has been widely used to forecast future result in various field for example art, biology, marketing including engineering. …”
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Final Year Project -
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Simultaneous Computation of Model Order and Parameter Estimation for System Identification Based on Gravitational Search Algorithm
Published 2015“…From the simulation, it is proven that the proposed method can be an alternative technique for solving the system identification problem. …”
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Reduced-rank technique for joint channel estimation in TD-SCDMA systems.
Published 2013“…Simulation results of the normalized mean square error for the above mentioned estimators showed the superiority of reduced rank estimators. …”
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Grouping based radio frequency identification anti-collision protocols for dense internet of things application
Published 2022“…This paper analyzes selected grouping-based algorithms. Their underlining principles are discussed including their tag estimation methods. …”
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Reduced rank technique for joint channel estimation and joint data detection in TD-SCDMA systems
Published 2013“…Simulation results of the normalized mean square error for the above mentioned estimators showed the superiority of reduced rank estimators. …”
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Detection of multiple outliners in linear regression using nonparametric methods
Published 2004“…REFERENCES Agullo, J. (2000). New Algorithms for Computing the Least Trimmed Squares Regression Estimator. …”
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