Abstract

This paper describes the use of a neural computational network model for pattern recognition and classification of aerodynamic particle size distributions associated with a number of environmental, bacterial, and artificial aerosols. The aerodynamic particle size distributions are measured in real time with high resolution using a two-spot He–Ne laser velocimeter. The technique employed here for the recognition and classification of aerosols of unknown origin is based on a three-layered neural network that has been trained on a training set consisting of 75 particle size distributions obtained from three distinct types of aerosols. The training of the neural network was accomplished with the back-propagation learning algorithm. The effects of the number of processing units in the hidden layer and the level of noise corrupting the training set, the test set, and the connection weights on the learning rate and classification efficiency of the neural network are studied. The ability of the trained network to generalize from the finite number of size distributions in the training set to unknown size distributions obtained from uncertain and unfamiliar environments is investigated. The approach offers the opportunity of recognizing, classifying, and characterizing aerosol particles in real time according to their aerodynamic particle size spectrum and its high recognition accuracy shows considerable promise for applications to rapid real-time air monitoring in the areas of occupational health and air pollution standards.

© 1990 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
Adaptive-clustering optical neural net

David P. Casasent and Etienne Barnard
Appl. Opt. 29(17) 2603-2615 (1990)

Subtracting incoherent optical neuron model: analysis, experiment, and applications

Chein-Hsun Wang and B. Keith Jenkins
Appl. Opt. 29(14) 2171-2186 (1990)

64-channel correlator implementing a Kohonen-like neural network for handwritten-digit recognition

M. Barge, K. Heggarty, Y. Idan, and R. Chevallier
Appl. Opt. 35(23) 4655-4665 (1996)

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Figures (17)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Tables (1)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Equations (6)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Metrics

You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription