Related papers: An adaptive sequential optimum design for model se…
This paper has been withdrawn by the author due to a crucial error in equation.
Machine learning assumes a pivotal role in our data-driven world. The increasing scale of models and datasets necessitates quick and reliable algorithms for model training. This dissertation investigates adaptivity in machine learning…
We consider non-parametric estimation problems in the presence of dependent data, notably non-parametric regression with random design and non-parametric density estimation. The proposed estimation procedure is based on a dimension…
This paper has been withdrawn by the author due to a crucial problem in Lemma 3. This equation must be changed.
For biological experiments aiming at calibrating models with unknown parameters, a good experimental design is crucial, especially for those subject to various constraints, such as financial limitations, time consumption and physical…
This paper presents adaptive observers for online state and parameter estimation of a class of nonlinear systems motivated by biophysical models of neuronal circuits. We first present a linear-in-the-parameters design that solves a…
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This paper has been withdrawn because of serious errors.
This supplement illustrates application of adaptive observer design from (Tyukin et al, 2013) for systems which are not uniquely identifiable. It also provides an example of adaptive observer design for a magnetic bearings benchmark system…
This paper has been withdrawn by the author.
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This paper has been withdrawn by the authors, due the copyright policy of the journal it has been submited to.
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This paper is withdrawn because the results in the paper are included in a paper to be published in Mathematical and Computer Modelling.
This paper has been withdrawn by the author due to incomplete interpretation for the results.
This paper has been withdrawn by the author due to a crucial sign error in equation 1
Dynamical systems, for instance in model predictive control, often contain unknown parameters, which must be determined during system operation. Online or on-the-fly parameter identification methods are therefore necessary. The challenge of…
This paper has been withdrawn by the author due to a crucial error in the formulation.
Recent research has shown the existence of significant redundancy in large Transformer models. One can prune the redundant parameters without significantly sacrificing the generalization performance. However, we question whether the…