Principles of artificial neural networks: hardware and software

Authors

  • Bonifacio Martín del Brío Departamento de Ingeniería Electrónica y Comunicaciones, Escuela Universitaria de Ingeniería Técnica Industrial, Universidad de Zaragoza, España
  • Carlos Serrano Cinca Departamento de Contabilidad y Finanzas, Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza, España

DOI:

https://doi.org/10.54886/scire.v1i1.1036

Abstract

Neural networks schematically model the hardware structure of our brain to reproduce its computational abilities. These parallel, distributed and adaptative processing systems are able to learn from experience, working on environmental data and by using numerical algorithms. This paper is an introduction to artificial neural networks. Firstly, basic features of the neuron model, network architecture and learning algorithms are presented. Secondly, the best known models of neural networks are described. Lastly, the different procedures for developing an artificial neural system are discussed, together with their possible applications to real world problems.

Downloads

Download data is not yet available.

Downloads

Published

1995-06-01

How to Cite

Martín del Brío, B., & Serrano Cinca, C. (1995). Principles of artificial neural networks: hardware and software. Scire: Knowledge Representation and Organization (ISSNe 2340-7042; ISSN 1135-3716), 1(1), 103–125. https://doi.org/10.54886/scire.v1i1.1036

Issue

Vol.1, N.1 (1995)

Section

Articles

License

Copyright (c) 1995 Authors retain their copyright, but transfer the exploitation rights (reproduction, distribution, public communication and transformation) to the journal in a non-exclusive way and guarantee the right to the first publication of their work to the journal, which will be simultaneously subjected to the license CC BY-NC-ND. Authors take whole personal responsibility on fulfilling all the appropiate ethical codes and laws, and obtaining all the necessary copyright permissions regarding their articles. Institutional and self- archiving is allowed and encouraged.

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

© 1996- . Authors retain their copyright, but transfer the exploitation rights (reproduction, distribution, public communication and transformation) to the journal in a non-exclusive way and guarantee the right to the first publication of their work to the journal, which will be simultaneously subjected to the license CC BY-NC-ND. Authors take whole personal responsibility on fulfilling all the appropiate ethical codes and laws, and obtaining all the necessary copyright permissions regarding their articles. Institutional and self- archiving is allowed and encouraged.