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The camera model identification problem is cast in the framework of hypothesis testing theory.
The goal of this paper is to design a statistical test for the camera model identification problem.
The goal of this paper is to design a statistical test for the camera model identification problem from JPEG images.
First, we considered the model identification problem as a classification problem to predict which model will be the most reliable for a given chemical compound.
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This paper discusses the importance and relevance of direct continuous-time system identification and how this relates to the solution for model identification problems in practical applications.
This ensures that a problem has a well defined solution independently of any method for solving it, and that the task of modelling identification problems is separated from the algorithmic task of solving given problems.
The remainder of the paper is organized as follows: The class of PWARX models and identification problem is stated in Section 2.
The model resolves the identification problem because any period effects that may arise between the different years of observation are controlled for in the model by κ.
Using the IPSO algorithm to minimize the mean square error (MSE) between the actual output and model output, the identification problem for nonlinear discrete-time systems can be fulfilled.
The formulation of the simultaneous model selection and identification problem is stated as an MINLP optimization problem.
This paper studies the modelling and identification problems for multi-input single-output (MISO) systems with colored noises.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com