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将是推导出信号处理的新算法，特别是对隐藏在噪声信号中的信息的估计。这将建立在申请者以前的贡献基础上。我们将朝三个方向努力。第一个部分将开发新的隐半马尔可夫模型估计算法，扩展了我们以前对隐马尔可夫模型的研究。第二种方法将考虑基于事件的过滤问题，当仅当隐藏信号变化超过指定量或当信号过程跨越某些级别时，才接收到观察到的过程。第三章将利用倒向随机微分方程讨论带噪声观测的马尔可夫链的最优控制问题。