NEURAL NETWORKS APPLIED TO TRANSIENT SIGNAL IDENTIFICATION

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Authors
  1. Swingler, D.N.
Corporate Authors
Defence Research Establishment Atlantic, Dartmouth NS (CAN);Saint Mary's Univ, Halifax NS (CAN) Div of Engineering
Abstract
This report details an investigation into the classification performance of a conventional, multi-layer perceptron, neural net and compares it to that of a classical k-Nearest Neighbour approach. The training and test vectors were derived from real underwater data provided by DREA. The results presented here indicate similar classification performance by each of the techniques.
Keywords
Transient detection;Back propagation
Report Number
DREA-CR-92-420 — Contractor Report
Date of publication
01 Mar 1992
Number of Pages
70
DSTKIM No
96-02420
CANDIS No
497173
Format(s):
Document Image stored on Optical Disk;Hardcopy

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