Estimation and filtering of hidden semi Markov models, event based filters and stochastic control.

隐半马尔可夫模型的估计和过滤、基于事件的过滤器和随机控制。

• 批准号: RGPIN-2015-06084
• 负责人: Elliott, Robert
• 金额: $ 2.19万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=637402
• 关键词: Estimation; filtering; hidden; semi; Markov

The central objective of the work will be the derivation of new algorithms for signal processing, in particular the estimation of information hidden in noisy signals. This will build on previous contributions by the applicant. Three directions will be pursued. The first will develop new estimation algorithms for hidden semi Markov models, extending our previous work on hidden Markov models. The second will consider event based filtering problems when the observed process is received only when the hidden signal changes by more than a specified amount or when the signal process crosses certain levels. The third will discuss the optimal control of a noisily observed Markov chain using backward stochastic differential equations.

这项工作的中心目标是推导出信号处理的新算法，特别是估计隐藏在嘈杂信号中的信息。这将建立在申请人以前的捐款基础上。将朝着三个方向努力。第一个将开发新的估计算法的隐半马尔可夫模型，扩展我们以前的工作隐马尔可夫模型。第二个将考虑基于事件的过滤问题时，所观察到的过程中，只有当隐藏的信号变化超过一个指定的量，或当信号过程跨越一定的水平。第三章讨论了基于倒向随机微分方程的噪声观测马尔可夫链的最优控制问题。