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

研究成果: 著書/レポートタイプへの貢献

3 引用 (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.

元の言語英語
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
出版者IGI Global
ページ239-254
ページ数16
ISBN(印刷物)9781615207114
DOI
出版物ステータス出版済み - 2010

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Neural networks

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

これを引用

Murata, J. (2010). Analysis and improvement of function approximation capabilities of pi-sigma higher order neural networks. : Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications (pp. 239-254). IGI Global. https://doi.org/10.4018/978-1-61520-711-4.ch010

Analysis and improvement of function approximation capabilities of pi-sigma higher order neural networks. / Murata, Junichi.

Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications. IGI Global, 2010. p. 239-254.

研究成果: 著書/レポートタイプへの貢献

Murata, J 2010, Analysis and improvement of function approximation capabilities of pi-sigma higher order neural networks. : Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications. IGI Global, pp. 239-254. https://doi.org/10.4018/978-1-61520-711-4.ch010
Murata J. Analysis and improvement of function approximation capabilities of pi-sigma higher order neural networks. : Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications. IGI Global. 2010. p. 239-254 https://doi.org/10.4018/978-1-61520-711-4.ch010
Murata, Junichi. / Analysis and improvement of function approximation capabilities of pi-sigma higher order neural networks. Artificial Higher Order Neural Networks for Computer Science and Engineering: Trends for Emerging Applications. IGI Global, 2010. pp. 239-254
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