Fundamental theory of artificial higher order neural networks

Madan M. Gupta, Noriyasu Homma, Zeng Guang Hou, Ashu M.G. Solo, Takakuni Goto

Research output: Chapter in Book/Report/Conference proceedingChapter

10 Citations (Scopus)

Abstract

In this chapter, we aim to describe fundamental principles of artificial higher order neural units (AHO-NUs) and networks (AHONNs). An essential core of AHONNs can be found in higher order weighted combinations or correlations between the input variables. By using some typical examples, this chapter describes how and why higher order combinations or correlations can be effective.

Original languageEnglish
Title of host publicationArtificial Higher Order Neural Networks for Economics and Business
PublisherIGI Global
Pages368-388
Number of pages21
ISBN (Print)9781599048970
DOIs
Publication statusPublished - 2008

ASJC Scopus subject areas

  • Computer Science(all)

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