The University of Dublin | Trinity College -- Ollscoil Átha Cliath | Coláiste na Tríonóide
Trinity's Access to Research Archive
Home :: Log In :: Submit :: Alerts ::

TARA >
School of Engineering >
Electronic & Electrical Eng >
Electronic & Electrical Eng (Scholarly Publications) >

Please use this identifier to cite or link to this item: http://hdl.handle.net/2262/19819

Title: Threshold learning from samples drawn from the null hypothesis for the generalized likelihood ratio cusum test
Other Titles: IEEE International Workshop on Machine Learning for Signal Processing
Author: KOKARAM, ANIL CHRISTOPHER
Sponsor: Science Foundation Ireland
Author's Homepage: http://people.tcd.ie/akokaram
Keywords: Electronic & Electrical Engineering
Issue Date: 2005
Citation: C. Hory, A. Kokaram and W. J. Christmas 'Threshold learning from samples drawn from the null hypothesis for the generalized likelihood ratio cusum test' in proceedings of IEEE International Workshop on Machine Learning for Signal Processing, Mystic, Connecticut, USA., 28-30 Sept., 2005, pp 111 - 116.
Abstract: Although optimality of sequential tests for the detection of a change in the parameter of a model has been widely discussed, the test parameter tuning is still an issue. In this communication, we propose a learning strategy to set the threshold of the GLR CUSUM statistics to take a decision with a desired false alarm probability. Only data before the change point are required to perform the learning process. Extensive simulations are performed to assess the validity of the proposed method. The paper is concluded by opening the path to a new approach to multi-modal feature based event detection for video parsing
Description: PUBLISHED
URI: http://ieeexplore.ieee.org/iel5/10270/32703/01532884.pdf?tp=&isnumber=32703&arnumber=1532884&punumber=10270
http://www.sigmedia.tv
http://hdl.handle.net/2262/19819
ISSN: 27120
Appears in Collections:Electronic & Electrical Eng (Scholarly Publications)

Files in This Item:

File Description SizeFormat
01532884.pdfIEEE pdf458.96 kBAdobe PDFView/Open


This item is protected by original copyright


Please note: There is a known bug in some browsers that causes an error when a user tries to view large pdf file within the browser window. If you receive the message "The file is damaged and could not be repaired", please try one of the solutions linked below based on the browser you are using.

Items in TARA are protected by copyright, with all rights reserved, unless otherwise indicated.

 

Valid XHTML 1.0! DSpace Software Copyright © 2002-2010  Duraspace - Feedback