Knowledge-based seismogram processing by mental images

dc.contributor.authorJoswig, Manfredde
dc.date.accessioned2009-07-10de
dc.date.accessioned2016-03-31T11:41:33Z
dc.date.available2009-07-10de
dc.date.available2016-03-31T11:41:33Z
dc.date.issued1994de
dc.date.updated2014-10-16de
dc.description.abstractThe impact of pictorial knowledge representation is demonstrated for two examples of time series analysis in seismology. The approaches perform a) automated recognition of known event signatures and b) high-resolution onset timing of later phases. Both methods work well under extreme conditions of noise and achieved human-like performance in recognizing known situations. Crucial for this success of pictorial knowledge representation was the design of suitably scaled images. They must be simple and robust enough to transform the complexity of “real life” data into a limited set of patterns. These patterns differ significantly from the initial data; they correspond more closely to the non-linear weighting of recognized impressions by an experienced scientist. Thus the author addresses the pictorial presentations as mental images. For both reported applications, part of their power comes by model-based image modifications. However, this enhancement is far from demanding a complete theory. Any fractional model already enhances the image adaptation, so mental images are best suited to deal with incomplete knowledge like any other artificial intelligence approach. Cognitive plausibility was found for both the non-linear image scalings and the model-based image modifications. In general, the author's method of pictorial knowledge representation conforms to the concept of mental images by Kosslyn. Any new task will demand the composition of new, dedicated image transformations where some generalized design criteria are derived from the author's applications.en
dc.identifier.other314416994de
dc.identifier.urihttp://nbn-resolving.de/urn:nbn:de:bsz:93-opus-41520de
dc.identifier.urihttp://elib.uni-stuttgart.de/handle/11682/6976
dc.identifier.urihttp://dx.doi.org/10.18419/opus-6959
dc.language.isoende
dc.rightsinfo:eu-repo/semantics/openAccessde
dc.subject.classificationSeismogrammde
dc.subject.ddc550de
dc.titleKnowledge-based seismogram processing by mental imagesen
dc.typearticlede
ubs.fakultaetFakultätsübergreifend / Sonstige Einrichtungde
ubs.institutSonstige Einrichtungde
ubs.opusid4152de
ubs.publikation.sourceIEEE transactions on systems, man, and cybernetics 24 (1994), S. 429-439. URL http://dx.doi.org./10.1109/21.278992de
ubs.publikation.typZeitschriftenartikelde

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