A New Smoothing Approach for Piecewise Smooth Functions: Application to Some Fundamental Functions
Lecture Notes in Networks and Systems, ISSN: 2367-3389, Vol: 476 LNNS, Page: 164-178
2023
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
This article is about a new smoothing method for piecewise smooth functions. This smoothing method is based on formulating any piecewise smooth function as the expectation of a discrete random variable. By adopting this formulation, we show that smoothing apiecewise smooth function is equivalent to smooth a probability distribution. In addition, we propose to use the Boltzmann distribution as a smoothing approximation for this probability distribution. We apply our smoothing approach to smooth some fundamental functions. The theoretical and numerical results show the efficiency of our method.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85137006316&origin=inward; http://dx.doi.org/10.1007/978-3-031-12416-7_14; https://link.springer.com/10.1007/978-3-031-12416-7_14; https://dx.doi.org/10.1007/978-3-031-12416-7_14; https://link.springer.com/chapter/10.1007/978-3-031-12416-7_14
Springer Science and Business Media LLC
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