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The Ocean Corpus Project - OCP


This is an auto generated reference to a document within the Ocean Corpus repository.  All rights reserved to the authors

Title

Passive Sonar Target Recognition Using a Back Propagating Neural Network

Authors

Summary

Continue on reverse if necessary and identify by block number The prompt and accurate processing of sonar data is essential in undersea warfare.The ability to quickly detect and classify sonar targets is crucial to the performance and survivability of all navy surface ships and submarines.With the advent of neural network technology, new opportuni- ties have arisen which could greatly enhance current sonar target recogni- tion capabilities.The main objective of this research is to demonstrate the practical usage of neural networks in recognizing the acoustic signatures of passive sonar targets using simulated-at-sea conditions.We will review the theory behind neural networks, the problems associated with recognizing acoustic signals in an underwater environment, and we wil make a detailed case study of a neural network's performance using test data generated from simulated sonar targets.CLASSIFICATION

Keywords

processing, performance survivability, technology, opportuni, objective, practical, signatures, simulated-at-sea conditionswe, underwater environment, targetsclassification securjty, securjty abstract, abstract iavailability, iavailability distribution, distribution unclassified, unclassified unlimited,

Links

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The Ocean Corpus project  aims to collect the largest number of publications relating to oceanography and marine science in a single database. The corpus is also used for Natural Language Processing.


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