Online hidden Markov model parameter estimation and minimax robust quickest change detection in uncertain stochastic processes
Data(s) |
2015
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Resumo |
Stochastic (or random) processes are inherent to numerous fields of human endeavour including engineering, science, and business and finance. This thesis presents multiple novel methods for quickly detecting and estimating uncertainties in several important classes of stochastic processes. The significance of these novel methods is demonstrated by employing them to detect aircraft manoeuvres in video signals in the important application of autonomous mid-air collision avoidance. |
Formato |
application/pdf |
Identificador | |
Publicador |
Queensland University of Technology |
Relação |
http://eprints.qut.edu.au/88476/1/Timothy_Molloy_Thesis.pdf Molloy, Timothy Liam (2015) Online hidden Markov model parameter estimation and minimax robust quickest change detection in uncertain stochastic processes. PhD thesis, Queensland University of Technology. |
Fonte |
School of Electrical Engineering & Computer Science; Science & Engineering Faculty |
Palavras-Chave | #Stochastic Processes #hidden Markov model #parameter estimation #quickest change detection #minimax robust #CUSUM rule #Shiryaev rule #relative entropy #manoeuvre detection #least favourable distributions #ODTA |
Tipo |
Thesis |