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  • 标题:Smoothing the High Level Canonical Piecewise-Linear Model by an Exponential Approximation of its Basis-Function
  • 本地全文:下载
  • 作者:Victor M. Jimenez-Fernandez ; Maribel Jimenez-Fernandez ; Hector Vazquez-Leal
  • 期刊名称:Computación y Sistemas
  • 印刷版ISSN:1405-5546
  • 出版年度:2016
  • 卷号:20
  • 期号:2
  • 页码:227-237
  • 语种:English
  • 出版社:Instituto Politécnico Nacional
  • 其他摘要:Piecewise-linear models constitute an attractive alternative to construct a function whose graph fits a finite set of discrete points. These models are preferably selected over other approximation strategies like polynomials or splines. Although there are several piecewise-linear models reported in literature, the so-called High Level Canonical has the remarkable advantage of emerging from a well-structured algorithmic methodology to efficiently determine the parameters of any given piecewise-linear function. However, as it happens in all other piecewise-linear models, it also has the problem of lack of differentiability at the breakpoints. In order to solve this problem, an approach based on an exponential approximation of the basis-function is proposed as a strategy to transform the High Level Canonical piecewise-linear model into a smooth-piecewise one. This mathematical transformation ensures the existence and continuity of the nth-order derivatives of the resulting smooth model. Besides of this, it is observed that by applying the piecewise-linear to smooth transformation, the number of terms of the resulting smooth representation can significantly be reduced due to a great number of them can be approximated by a line equation. In order to verify the effectiveness of this proposal, numerical simulations performed on one-dimensional and two-dimensional functions are reported.
  • 其他关键词:High-Level-Canonical; piecewise-linear; smoothing; basis-function; approximation.
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