Abstract
This chapter describes basic neural computing architectures and learning algorithms targeted for implementation in later chapters. It is intended for the reader seeking an abstract and simple introduction to neural computing architectures and learning algorithms.We first describe a basic neural computing framework, and then review the perceptron, multi-layer perceptron, and associated learning algorithms.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1996 M.A. Jabri, R.J. Coggins and B.G Flower
About this chapter
Cite this chapter
Jabri, M.A., Coggins, R.J., Flower, B.G. (1996). Introduction to neural computing. In: Adaptive Analog VLSI Neural Systems. Springer, Dordrecht. https://doi.org/10.1007/978-94-011-0525-5_2
Download citation
DOI: https://doi.org/10.1007/978-94-011-0525-5_2
Publisher Name: Springer, Dordrecht
Print ISBN: 978-0-412-61630-3
Online ISBN: 978-94-011-0525-5
eBook Packages: Springer Book Archive