An Overview of Sequential Learning Algorithms for Single Hidden Layer
Networks: Current Issues & Future Trends
Abstract
This paper serves as an overview for sequential learning algorithms for
single hidden layer neural nets. Cite as: M. H. Arshad, M. A. Abido. An
Overview of Sequential Learning Algorithms for Single Hidden Layer
Networks: Current Issues & Future Trends. Abstract: In this paper, a
brief survey of the commonly used sequential-learning algorithms used
with single hidden layer feed-forward neural networks is presented. A
glimpse at the different kinds that are available in the literature up
until now, how they have developed throughout the years, and their
relative execution is summarized. Most important things to take note of
during the designing phase of neural networks are its complexity,
computational efficiency, maximum training time, and ability to
generalize the under-study problem. The comparison of different
sequential learning algorithms in regard to these merits for single
hidden layer neural networks is drawn.