Fundamental Theory of Artificial Higher Order Neural Networks

Abstract

In this chapter, we aim to describe fundamental principles of artificial higher order neural units (AHONUs) 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. Request access from your librarian to read this chapter's full text.