利用神经网络估计边缘四叉树的节点数

F.A Schreiber, R.Calvo Wolfler
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引用次数: 4

摘要

边四叉树的节点数是其空间复杂度的度量。这个数字取决于图形的形状、分辨率和精度。本工作的目的是证明边四叉树的节点数与这三个参数之间存在关系。为了达到这一目标,采用了一种实验方法。使用一个唯一的值来表示分辨率和精度。为了测量图像的形状,我们使用分形维数。提出了一种计算分形维数和分形测度的方法。给定这三个参数后,我们使用神经网络来逼近所求函数。计算结果表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。
Use of Neural Networks to Estimate the Number of Nodes of an Edge Quadtree

The number of nodes of an edge quadtree is the measure of its space complexity. This number depends on the figure's shape, its resolution and its precision. The goal of this work is to prove that a relation exists between the number of nodes of an edge-quadtree and these three parameters. To reach this goal an experimental approach has been used. A unique value to represent both the resolution and the precision is used. To measure the shape of the image we use the fractal dimension. A methodology to calculate the fractal dimension and the fractal measure is proposed. These three parameters being given, we use a neural network to approximate the sought function. The computational results show the effectiveness of this approach.

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