Analysis and improvement of function approximation capabilities of pi-sigma higher order neural networks

研究成果: Chapter in Book/Report/Conference proceedingChapter

3 被引用数 (Scopus)

抄録

A Pi-Sigma higher order neural network (Pi-Sigma HONN) is a type of higher order neural network, where, as its name implies, weighted sums of inputs are calculated first and then the sums are multiplied by each other to produce higher order terms that constitute the network outputs. This type of higher order neural networks have good function approximation capabilities. In this chapter, the structural feature of Pi-Sigma HONNs is discussed in contrast to other types of neural networks. The reason for their good function approximation capabilities is given based on pseudo-theoretical analysis together with empirical illustrations. Then, based on the analysis, an improved version of Pi-Sigma HONNs is proposed which has yet better function approximation capabilities.

本文言語英語
ホスト出版物のタイトルArtificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications
出版社IGI Global
ページ239-254
ページ数16
ISBN(印刷版)9781615207114
DOI
出版ステータス出版済み - 2010

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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