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1
Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms
Published 2022“…In diffusion estimation of distributed networks two characteristic parameters are crucial, the speed of convergence and steady-state error. …”
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Proceedings -
2
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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3
Dynamic robust bootstrap method based on LTS estimators
Published 2009“…In order to make reliable inferences about the parameters of a model, require that the parameter estimates are normally distributed. …”
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4
Statistical approach on grading: mixture modeling
Published 2006“…A solution to this problem is using the Markov Chain Monte Carlo method namely Gibbs sampler algorithm. …”
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5
Modeling The Modified Internal Rate Of Return (Mirr) For Long-Term Investment Strategy By The Assumption Of Gamma Distribution
Published 2023“…The estimation of the shape and scale parameters of the gamma distribution is relatively straightforward using the method of moments. …”
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6
Statistical approach on grading the student achievement via normal mixture modeling
Published 2006“…Statistical approaches which used the Standard Deviation (GC) and conditional Bayesian methods are considered to assign the grades. In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution where the grades are distinctively separated by the parameters: means and proportions of the Normal Mixture distribution. …”
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7
Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin
Published 2011“…The Resilient Backpropagation (RPROP) algorithm is used to train the network. The optimized learning parameter used is 0.07 and the network has best performance when hidden neurons equal to 220. …”
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8
REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC
Published 2011“…However, the rate cannot be exactly calculated at the encoder, instead it can only be estimated. This work also prbposes a feedback-free region-based adaptive DVC solution in pixel domain based on machine learning approach to estimate the side information. …”
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9
Machine condition monitoring and fault diagnosis using spectral analysis techniques
Published 2001“…Vibration data are collected from the piezoelectric accelerometers placed at locations that provide rigid vibration transmission to them. Both normal and fault signals are analyzed using the singular value decomposition (SVD) algorithm so as to compute the parameters of the auto regressive moving average (ARMA) models. …”
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Proceeding Paper -
10
Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…A computationally simple two-step iterative algorithm, called estimationapproximation algorithm, is introduced for estimating the parameters of the model on the basis of the rank estimators. …”
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11
Channel Modelling and Estimation in Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing Wireless Communication Systems
Published 2008“…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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12
An Improved Scatter Search Algorithm for Parameter Estimation in Large-Scale Kinetic Models of Biochemical Systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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13
An improved scatter search algorithm for parameter estimation in large-scale kinetic models of biochemical systems
Published 2019“…Methods: This paper proposes an improved scatter search algorithm to address the challenging parameter estimation problem. …”
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14
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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15
Parameter Estimation Using Improved Differential Evolution And Bacterial Foraging Algorithms To Model Tyrosine Production In Mus Musculus(Mouse)
Published 2015“…The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimisation method implemented to obtain the best kinetic parameter value. …”
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16
Parameter estimation of tapioca starch hydrolysis process: Application of least squares and genetic algorithm
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17
An enhanced segment particle swarm optimization algorithm for kinetic parameters estimation of the main metabolic model of Escherichia coli
Published 2020“…In this study, an Enhanced Segment Particle Swarm Optimization algorithm (ESe-PSO) was proposed for kinetic parameters estimation. …”
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18
PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…Results suggest that the PSO algorithm is viable alternative to other established algorithms for LLS parameter estimation. …”
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19
Parameter estimation of tapioca starch hydrolysis process: application of least squares and genetic algorithm
Published 2005“…The performance of genetic algorithm (GA) in nonlinear kinetic parameter estimation of topiaca starch hydrolysis was studied and compared with Gauss-Newton method. …”
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20
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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