000	00000nam 2200000zi 4500
001	9.950365
003	CaOODSP
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008	250423e199203##nscad   ob   f000 0 eng d
040	|aCaOODSP|beng|erda|cCaOODSP
041	0 |aeng|beng|bfre
086	1 |aD68-20/3-1992E-PDF
100	1 |aSwingler, D. N., |eauthor.
245	10|aNeural networks applied to transient signal identification / |cby D.N. Swingler.
264	1|aHalifax, Nova Scotia : |bDefence Research Establishment Atlantic = Centre de recherches pour la défense atlantique : |bNational Defence, Research and Development Branch = Défense nationale, Bureau de recherche et développement, |cMarch 1992.
300	|a1 online resource (1 volume (various pagings)) : |billustrations, graphs.
336	|atext|btxt|2rdacontent
337	|acomputer|bc|2rdamedia
338	|aonline resource|bcr|2rdacarrier
490	1 |aDREA CR ; |v92/420
500	|a"W7707-9-01274/01-OSC Contract Number."
500	|aDigitized edition from print [produced by Defence Research and Development Canada].
504	|aIncludes bibliographical references (page 36).
520	|a"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"--Abstract, page 6.
546	|aIncludes abstracts in English and French.
650	0|aNeural networks (Computer science)
650	0|aSignal processing.
650	6|aRéseaux neuronaux (Informatique)
650	6|aTraitement du signal.
710	2 |aDefence Research Establishment Atlantic, |eissuing body.
710	1 |aCanada. |bDepartment of National Defence. |bResearch and Development Branch, |eissuing body.
830	#0|aContractor report (Defence Research Establishment Atlantic)|v92/420.|w(CaOODSP)9.941814
856	40|qPDF|s4.58 MB|uhttps://publications.gc.ca/collections/collection_2025/rddc-drdc/D68-20-3-1992-eng.pdf