Search Results - "de Kruif, Bas J."

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  1. 1

    Simulation Architecture for Modelling Interaction Between User and Elbow-articulated Exoskeleton by de Kruif, Bas J., Schmidhauser, Emilio, Stadler, Konrad S., O’Sullivan, Leonard W.

    Published in Journal of bionics engineering (01-10-2017)
    “…The aim of our work is to improve the existing user-exoskeleton models by introducing a simulation architecture that can simulate its dynamic interaction,…”
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    Journal Article
  2. 2

    Autonomous docking of a feeder vessel by de Kruif, Bas J.

    “…Autonomous sailing is seen as one of the possible solutions to cope with the decrease in qualified personnel and to minimise the risk to humans and ships in…”
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    Journal Article
  3. 3

    Control of a full port-to-port mission for a feeder vessel by de Kruif, Bas J., van Daalen, Ed F. G., Cozijn, H., Iavicoli, G.

    Published in OCEANS 2023 - Limerick (05-06-2023)
    “…Autonomy is posed as a solution to decrease the amount of qualified personnel on a ship. It would be especially advantageous for those tasks that are dirty,…”
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    Conference Proceeding
  4. 4

    Wet-etch sequence optimisation incorporating time dependent chemical maintenance by de Kruif, Bas J.

    “…Wafer fabrication is the major cost contributor in semiconductor manufacturing. One of the steps in the fabrication is the removal of exposed layers in an…”
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    Conference Proceeding
  5. 5

    Quay-to-quay mission with autonomous docking: a model-scale experimental validation by de Kruif, Bas J., van Daalen, Ed F. G., Cozijn, Hans, Iavicoli, Giorgio

    “…Transport of cargo by short-sea shipping is at the forefront of the European Union's transportation policy. It has the promise to alleviate congested land…”
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    Journal Article
  6. 6

    Pruning error minimization in least squares support vector machines by de Kruif, B.J., de Vries, T.J.A.

    Published in IEEE transactions on neural networks (01-05-2003)
    “…The support vector machine (SVM) is a method for classification and for function approximation. This method commonly makes use of an /spl epsi/-insensitive…”
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    Journal Article
  7. 7

    Classification of Imagined Beats for use in a Brain Computer Interface by de Kruif, B.J., Schaefer, R., Desain, P.

    “…The power spectrum of an EEG signal shows differences with respect to its baseline the moment a subject is hearing, or expecting, a tone. As this difference…”
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    Conference Proceeding Journal Article
  8. 8

    Self-Propulsion Parameter Identification for Control of Marin's AUV by de Kruif, Bas J., Ypma, Egbert

    “…Marin designed and built a modular autonomous underwater vehicle to be used in its model basins. In order to improve the control design, as well as its digital…”
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    Conference Proceeding
  9. 9

    Designing a Multi Trial Classifier for EEG Signals: Classifying Rhythms Perceived by de Kruif, B.J., Desain, P.

    “…Classification of EEG-signals is error-prone, due to the the small differences in the measurements and the inherent presence of continuing brain dynamics…”
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    Conference Proceeding
  10. 10

    Comparison of four support-vector based function approximators by de Kruif, B.J., de Vries, T.J.A.

    “…One of the uses of the support vector machine (SVM), as introduced in V.N. Vapnik (2000), is as a function approximator. The SVM and approximators based on it,…”
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    Conference Proceeding
  11. 11

    Support-vector-based least squares for learning non-linear dynamics by de Kruif, B.J., de Vries, T.J.A.

    “…A function approximator is introduced that is based on least squares support vector machines (LSSVM) and on least squares (LS). The potential indicators for…”
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    Conference Proceeding
  12. 12

    On-line nonparametric regression to learn state-dependent disturbances by de Kruif, B.J., de Vries, T.J.A.

    “…A combination of recursive least squares and weighted least squares is made which can adapt its structure such that a relation between in- and output can be…”
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    Conference Proceeding