2020
DOI: 10.2478/amns.2020.2.00057
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Small C 1-smooth perturbations of skew products and the partial integrability property

Abstract: In this paper we investigate stability of the integrability property of skew products of interval maps under small C1-smooth perturbations satisfying some conditions. We obtain here (sufficient) conditions of the partial integrability for maps under considerations. These conditions are formulated in the terms of properties of the unperturbed skew product. We give also the example of the partially integrable map.

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Cited by 13 publications
(6 citation statements)
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“…Two principles should be followed when comparing indicators: (1) determine the weight according to the amount of information [11]. The index weight value with more information is large, on the contrary, the index weight value with less information is small.…”
Section: Experiments and Discussionmentioning
confidence: 99%
“…Two principles should be followed when comparing indicators: (1) determine the weight according to the amount of information [11]. The index weight value with more information is large, on the contrary, the index weight value with less information is small.…”
Section: Experiments and Discussionmentioning
confidence: 99%
“…Compared with the dispersion method, the percentile method not only has the advantages of the dispersion method, but also uses the median as the reference value and other percentiles as the discrete distance to divide the evaluation grade, instead of taking the average as the reference value and the standard deviation as the discrete distance. It is applicable to all kinds of data with normal distribution or non normal distribution, and also reduces the link that the normal test must be carried out on relevant data because the distribution characteristics of data are not clear before formulating the evaluation standard [13]. Especially for non normal distribution data, it can be evaluated more accurately.…”
Section: Experiments and Discussionmentioning
confidence: 99%
“…The transformation function of the node selects the sigmoid function. The initial weight is between (-1, 1), which is randomly generated [15]. The learning step size is determined to be 0.1,Figure 4 is the learning result, and Figure 5 is the error curve.…”
Section: Figure 3model Diagram Of Teaching Quality Evaluation Based O...mentioning
confidence: 99%