Accession Number:

ADA230739

Title:

Performance of Neural Networks in Classifying Environmentally Distorted Transient Signals

Descriptive Note:

Proceedings rept.

Corporate Author:

NAVAL OCEANOGRAPHIC AND ATMOSPHERIC RESEARCH LAB STENNIS SPACE CENTER MS

Personal Author(s):

• Field, R. L.
• Yoerger, E. J.
• Simpson, P. K.

Report Date:

1990-01-01

Pagination or Media Count:

6.0

Abstract:

Neutral networks have been showing great promise in several areas, one of which is the classification of underwater acoustic transients. The classification of low-frequency underwater acoustic transient signals using a neural network based system is investigated. The received acoustic transients are simulated using a time-domain parabolic equation model. The neural network is trained on three source signals and tested by classifying the same signals at 25 different receiver locations in a noise-free, range-dependent upslope environment. Overall classification performance is above 90.

Descriptors:

• *TRANSIENTS
• POSITION(LOCATION)
• NEURAL NETS
• ENVIRONMENTS
• UNDERWATER ACOUSTICS
• NEUTRAL
• SIGNALS
• RECEIVERS
• CLASSIFICATION
• ACOUSTICS
• SOURCES
• NETWORKS

Subject Categories:

• Computer Systems
• Acoustic Detection and Detectors

Distribution Statement:

APPROVED FOR PUBLIC RELEASE