Uncertainty coding and controlled data reduction using fuzzy-B-splines

G. Gallo, M. Spagnuolo
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引用次数: 12

Abstract

In this paper, a method is described for the representation and reconstruction of single-valued surfaces given as sets of measured data, which may be uncertain as well as crisp. In the case of imprecise data, the fuzzy B-spline representation is able to keep track of uncertainty and provide tools for interrogating the model at prescribed presumption levels. In both cases, a very high degree of compression can be achieved through a procedure which defines, among spatially-clustered points, the most significant representative of the local neighbourhood. Experimental results are shown to prove the effectiveness of the proposed approach.
不确定性编码与模糊b样条控制数据约简
本文描述了一种以测量数据集形式给出的单值曲面的表示和重构方法。在数据不精确的情况下,模糊b样条表示能够跟踪不确定性,并为在规定的推定水平上询问模型提供工具。在这两种情况下,通过在空间聚类点中定义本地邻域的最重要代表的过程,可以实现非常高程度的压缩。实验结果证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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