Theoretical and experimental analysis of the first layer in neural     networks for 3D pattern recognition

Jesus Figueroa-Nazuno; A. Vazquez-Nava; E. Vargas Medina

doi:10.1117/12.140106

1 July 1992 Theoretical and experimental analysis of the first layer in neural networks for 3-D pattern recognition

Jesus Figueroa-Nazuno, A. Vazquez-Nava, E. Vargas Medina

Proceedings Volume 1710, Science of Artificial Neural Networks; (1992) https://doi.org/10.1117/12.140106
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

The behavior of the first layer of a weightless artificial neural network is analyzed in this paper. The way in which the neural network receives external information changes according to different probability distribution functions that control data sampling from many different patterns. This paper describes the architecture of this system, and shows the effect of the different probability distribution functions over 3-dimensional pattern recognition.

Citation Download Citation

Jesus Figueroa-Nazuno, A. Vazquez-Nava, and E. Vargas Medina "Theoretical and experimental analysis of the first layer in neural networks for 3-D pattern recognition", Proc. SPIE 1710, Science of Artificial Neural Networks, (1 July 1992); https://doi.org/10.1117/12.140106

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available