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Record Details

Record 12 of 155
Semi-Supervised Novelty Detection with Adaptive Eigenbases, and Application to Radio Transients
External Online Source: hdl:2014/43774
Author and Affiliation:
Thompson, David R.(Jet Propulsion Lab., California Inst. of Tech., Pasadena, CA, United States)
Majid, Walid A.(Jet Propulsion Lab., California Inst. of Tech., Pasadena, CA, United States)
Reed, Colorado J.(Jet Propulsion Lab., California Inst. of Tech., Pasadena, CA, United States)
Wagstaff, Kiri L.(Jet Propulsion Lab., California Inst. of Tech., Pasadena, CA, United States)
Abstract: We present a semi-supervised online method for novelty detection and evaluate its performance for radio astronomy time series data. Our approach uses adaptive eigenbases to combine 1) prior knowledge about uninteresting signals with 2) online estimation of the current data properties to enable highly sensitive and precise detection of novel signals. We apply the method to the problem of detecting fast transient radio anomalies and compare it to current alternative algorithms. Tests based on observations from the Parkes Multibeam Survey show both effective detection of interesting rare events and robustness to known false alarm anomalies.
Publication Date: Oct 19, 2011
Document ID:
20150006638
(Acquired Apr 27, 2015)
Subject Category: ASTROPHYSICS; ASTRONOMY
Document Type: Conference Paper
Meeting Information: Conference on Intelligent Data Understanding (CIDU 2011); 19-21 Oct. 2011; Mountain View, CA; United States
Meeting Sponsor: NASA; Washington, DC, United States
NASA Ames Research Center; Moffett Field, CA, United States
Notre Dame Univ.; Notre Dame, IN, United States
Financial Sponsor: Jet Propulsion Lab., California Inst. of Tech.; Pasadena, CA, United States
Organization Source: Jet Propulsion Lab., California Inst. of Tech.; Pasadena, CA, United States
Description: 11p; In English
Distribution Limits: Unclassified; Publicly available; Unlimited
Rights: Copyright
NASA Terms: SIGNAL DETECTION; ALGORITHMS; EIGENVALUES; TRANSIENT RESPONSE; RATES (PER TIME); TIME LAG; SIGNAL DISTORTION; ANOMALIES; FALSE ALARMS; DATA PROCESSING; RADIO SOURCES (ASTRONOMY); MATHEMATICAL MODELS; SENSITIVITY; SKY SURVEYS (ASTRONOMY); RADIO ASTRONOMY; TIME SERIES ANALYSIS
Other Descriptors: RADIO TRANSIENTS; RADIO ASTRONOMY; ANOMALY DETECTION; TIME SERIES ANALYSIS; MACHINE LEARNING
Availability Source: Other Sources
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