165 research outputs found

    New Way of As2S3 Microtubules Preparation by Roll Up Thin Films Synthesized at the Air-Solution Interface

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    For the first time the conditions of synthesis As2S3 microtubules were defined. Investigation of the synthesized scroll-like structures was carried out by optical microscopy, scanning electron microscopy, electron microprobe analysis, X-ray diffraction, and Raman spectroscope. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3093

    As2S3 Thin Films Synthesized in “Soft Chemistry” Conditions and Microtubules From Them

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    For the first time the conditions of synthesis As2S3 microtubules were defined. Investigation of the synthesized scroll-like structures was carried out by optical microscopy, scanning electron microscopy, electron microprobe analysis, X-ray diffraction, and Raman spectroscope. When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3500

    Spectral identification in networks of pulse-coupled oscillators

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    Spectral identification in networks of pulse-coupled oscillators

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    Two methods to approximate the Koopman operator with a reservoir computer

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    The Koopman operator provides a powerful framework for data-driven analysis of dynamical systems. In the last few years, a wealth of numerical methods providing finite-dimensional approximations of the operator have been proposed (e.g. extended dynamic mode decomposition (EDMD) and its variants). While convergence results for EDMD require an infinite number of dictionary elements, recent studies have shown that only few dictionary elements can yield an efficient approximation of the Koopman operator, provided that they are well-chosen through a proper training process. However, this training process typically relies on nonlinear optimization techniques. In this paper, we propose two novel methods based on a reservoir computer to train the dictionary. These methods rely solely on linear convex optimization. We illustrate the efficiency of the method with several numerical examples in the context of data reconstruction, prediction, and computation of the Koopman operator spectrum. These results pave the way to the use of the reservoir computer in the Koopman operator framework
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