REAL-TIME RECOGNITION OF TIME-SERIES PATTERNS
| dc.contributor.author | Morrill, Jeffrey P. | |
| dc.contributor.author | Delatizky, Jonathan | |
| dc.date.accessioned | 2016-05-10T16:48:50Z | en |
| dc.date.available | 2016-05-10T16:48:50Z | en |
| dc.date.issued | 1993-10 | en |
| dc.identifier.issn | 0884-5123 | en |
| dc.identifier.issn | 0074-9079 | en |
| dc.identifier.uri | http://hdl.handle.net/10150/608854 | en |
| dc.description | International Telemetering Conference Proceedings / October 25-28, 1993 / Riviera Hotel and Convention Center, Las Vegas, Nevada | en_US |
| dc.description.abstract | This paper describes a real-time implementation of the pattern recognition technology originally developed by BBN [Delatizky et al] for post-processing of time-sampled telemetry data. This makes it possible to monitor a data stream for a characteristic shape, such as an arrhythmic heartbeat or a step-response whose overshoot is unacceptably large. Once programmed to recognize patterns of interest, it generates a symbolic description of a time-series signal in intuitive, object-oriented terms. The basic technique is to decompose the signal into a hierarchy of simpler components using rules of grammar, analogous to the process of decomposing a sentence into phrases and words. This paper describes the basic technique used for pattern recognition of time-series signals and the problems that must be solved to apply the techniques in real time. We present experimental results for an unoptimized prototype demonstrating that 4000 samples per second can be handled easily on conventional hardware. | |
| dc.description.sponsorship | International Foundation for Telemetering | en |
| dc.language.iso | en_US | en |
| dc.publisher | International Foundation for Telemetering | en |
| dc.relation.url | http://www.telemetry.org/ | en |
| dc.rights | Copyright © International Foundation for Telemetering | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | |
| dc.subject | pattern recognition | en |
| dc.subject | real-time analysis | en |
| dc.subject | signal processing | en |
| dc.subject | time-series data | en |
| dc.title | REAL-TIME RECOGNITION OF TIME-SERIES PATTERNS | en_US |
| dc.type | text | en |
| dc.type | Proceedings | en |
| dc.contributor.department | Bolt, Beranek, and Newman Inc. | en |
| dc.identifier.journal | International Telemetering Conference Proceedings | en |
| dc.description.collectioninformation | Proceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection. | en |
| refterms.dateFOA | 2018-09-11T10:07:39Z | |
| html.description.abstract | This paper describes a real-time implementation of the pattern recognition technology originally developed by BBN [Delatizky et al] for post-processing of time-sampled telemetry data. This makes it possible to monitor a data stream for a characteristic shape, such as an arrhythmic heartbeat or a step-response whose overshoot is unacceptably large. Once programmed to recognize patterns of interest, it generates a symbolic description of a time-series signal in intuitive, object-oriented terms. The basic technique is to decompose the signal into a hierarchy of simpler components using rules of grammar, analogous to the process of decomposing a sentence into phrases and words. This paper describes the basic technique used for pattern recognition of time-series signals and the problems that must be solved to apply the techniques in real time. We present experimental results for an unoptimized prototype demonstrating that 4000 samples per second can be handled easily on conventional hardware. |
