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

Junichi Murata

Research output: Chapter in Book/Report/Conference proceedingChapter

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Title of host publicationArtificial Higher Order Neural Networks for Computer Science and Engineering
Subtitle of host publicationTrends for Emerging Applications
PublisherIGI Global
Pages239-254
Number of pages16
ISBN (Print)9781615207114
DOIs
Publication statusPublished - 2010

All Science Journal Classification (ASJC) codes

  • General Computer Science

Fingerprint

Dive into the research topics of 'Analysis and improvement of function approximation capabilities of pi-sigma higher order neural networks'. Together they form a unique fingerprint.

Cite this