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The approach for parameter estimation is based on that in [11].
To achieve the goal, a model-based design of experiment (MBDOE) approach for parameter estimation is employed.
The paper presents a direct adaptive fuzzy approach for parameter identification and control of unknown nonlinear systems.
If an adequate probabilistic framework can be specified for a sample data set, maximum likelihood [ML] typically provides an efficient approach for parameter estimation.
The proposed approach for parameter estimation is capable of estimating unknown parameters even away from the broadside of the beam pattern.
The conventional approach for parameter evaluation of non-linear forms of aforementioned isotherms involves linearization of the expressions through transformation, followed by the linear regression method.
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The inference approach used is based on a GEV distribution and a Bayesian Monte Carlo Markov Chain approach for parameters estimation.
This paper proposes two novel approaches for parameter estimation of a superpositional intonation model.
Several approaches for parameter estimation were proposed in the literature but the maximum likelihood method is the most commonly employed.
Several approaches for parameter point estimation were proposed in the literature but the maximum likelihood method is the most commonly employed.
Therefore there remains a need to develop rigorous modern statistical approaches for parameter estimation of non-linear models for the 2001 FMD outbreak.
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