Research on Construction of Multiwavelets Using Hopfield Neural Networks

机译：Hopfield神经网络构造多小波的研究

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There has been a growing research interest in the areas of construction and application of multiwavelets over the past few years. The construction of multiwavelets with some specified property will be required the solution of large and complex system of nonlinear design equations. In this paper, we construct multiwavelets with some good properties by Hopfield feedback neural networks instead of by software Singular, which is in most common use at present. Our methord can not only obtain the satisfied solutions when the proper initial values are chosen, but also get over the mass time-cost by Singular carrying out the Gobner basis computations.

机译：在过去的几年中，对多小波的构建和应用领域的研究兴趣日益增长。具有大型特性的多小波的构造将是解决大型和复杂的非线性设计方程组的要求。在本文中，我们通过Hopfield反馈神经网络而不是目前最常用的软件Singular构造具有良好性能的多小波。我们的方法不仅可以在选择合适的初始值时获得满意的解，而且可以通过奇异的Gobner基计算来克服大量的时间成本。

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《World Multiconference on Systemics, Cybernetics and Informatics(SCI 2002) v.6: Industrial Systems and Engineering I; 20020714-20020718; Orlando,FL; US》|2002年|P.461-466|共6页
会议地点 Orlando FL(US);Orlando FL(US)
作者
Xieping Gao; Caiyan Jia;
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作者单位

Xiangtan University Hunan, 411105, PRC;

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会议组织
原文格式 PDF
正文语种 eng
中图分类计算技术、计算机技术;
关键词
multiwavelets; general cardinal; grobner bases; singular; hopfield neural networks;

机译：多小波;一般基数; Grobner底基;奇异;跳场神经网络;

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4. Research on Construction of Multiwavelets Using Hopfield Neural Networks [C] . Xieping Gao, Caiyan Jia World Multi-conference on Systemics, Cybernetics and Informatics . 2002

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Research on Construction of Multiwavelets Using Hopfield Neural Networks

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