NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Self-organizing map (SOM) of space acceleration measurement system (SAMS) dataIn this paper, space acceleration measurement system (SAMS) data have been classified using self-organizing map (SOM) networks without any supervision; i.e., no a priori knowledge is assumed regarding input patterns belonging to a certain class. Input patterns are created on the basis of power spectral densities of SAMS data. Results for SAMS data from STS-50 and STS-57 missions are presented. Following issues are discussed in details: impact of number of neurons, global ordering of SOM weight vectors, effectiveness of a SOM in data classification, and effects of shifting time windows in the generation of input patterns. The concept of 'cascade of SOM networks' is also developed and tested. It has been found that a SOM network can successfully classify SAMS data obtained during STS-50 and STS-57 missions.
Document ID
20040119942
Acquisition Source
Glenn Research Center
Document Type
Reprint (Version printed in journal)
Authors
Sinha, A.
(University Park 16802 United States)
Smith, A. D.
Date Acquired
August 22, 2013
Publication Date
January 1, 1999
Publication Information
Publication: Microgravity science and technology
Volume: 12
Issue: 2
ISSN: 0938-0108
Subject Category
Life Sciences (General)
Funding Number(s)
CONTRACT_GRANT: NAG3-1586
Distribution Limits
Public
Copyright
Other
Keywords
STS-57 Shuttle Project
Flight Experiment
STS-50 Shuttle Project
short duration
manned

Available Downloads

There are no available downloads for this record.
No Preview Available