Filtering and Parameter Estimation for a Class of Hidden Markov Models with Application to Bubble-Counting in Microfluidics

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• 作者：Francesco Carravetta^* ; ^{francesco.carravetta@iasi.cnr.it" class="auth_mail" title="E-mail the corresponding author} ; Costanzo Manes^** ; ^{costanzo.manes@univaq.it" class="auth_mail" title="E-mail the corresponding author} ; Pasquale Palumbo^* ; ^{pasquale.palumbo@iasi.cnr.it" class="auth_mail" title="E-mail the corresponding author}
• 关键词：Markov Models ; Parameter Identification ; System State Estimation
• 刊名：IFAC-PapersOnLine
• 出版年：2014
• 出版时间：2014
• 年：2014
• 卷：47
• 期：3
• 页码：9540-9544
• 全文大小：236 K

文摘

Motivated by a practical problem, in this work we investigate the problem of simultaneous estimation of state and parameters of an Hidden Markov Model with a particular structure. The motivating application is the problem of automatic counting of bubbles or droplets flowing into a microfluidic channel, where the noisy output of a photodiode has to be processed in order to detect the transit of bubbles. The goal is achieved through the recursive computation of a pseudo-max-likelihood estimate.