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讨论基于自动机/形式语言模型的离散事件系统(DES)的可测性问题。可测性即为根据系统的可观事件和状态输出的信息估计系统的当前状态。定义了四种可测性:强可测性,弱可测性,强周期可测性,弱周期可测性。给出了这些可测性的充要条件,这些充要条件可通过构建观测器进行有效的判定。 相似文献
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讨论基于自动机/形式语言模型的离散事件系统(DES)稳定性问题,引入了确定性离散事件系统N步稳定性定义,并得到了稳定性的判据定理,推导了具体的算法实现。该算法具有多项式复杂度。 相似文献
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In this paper, we extend our previous results on detectability to nondeterministic discrete event systems. Many practical systems are nondeterministic, especially those in biomedicine. Disease models of patients are usually nondeterministic because hardly anything is deterministic in biological systems. The goal is to determine or estimate the current and subsequent states of a system based on a sequence of observations when the initial state of the system is unknown. We say that a system is detectable if one can determine its state after observing some outputs. The observation includes partial event observation and/ or partial state observation. We define four types of detectabilities: strong detectability, (weak) detectability, strong periodic detectability, and (weak) periodic detectability. We derive necessary and sufficient conditions for these detectabilities. These conditions can be checked by constructing an observer, which models the estimation of states under different observation. Furthermore, we apply the results to medical diagnosis by considering a realistic example of diagnosing whether a patient suffers from one of the following five similar diseases : ( 1 ) rheumatoid arthritis, (2) rheumatic arthritis, ( 3 ) systemic lupus eruthematosus, (4) bony ankylosis, or ( 5 ) spondylitis ankylopoietica. 相似文献
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本文讨论基于非确定自动机,形式语言模型的非确定离散事件系统稳定性的多项式算法.在引入拟距离的概念之后.根据拟距离形式化地定义了非确定离散事件系统稳定性.以往判定非确定离散事件系统稳定性的算法基于系统的观测器实现,该观测器在结构上具有指数复杂度,因此本文分析系统结构和观测器结构之间的关系,基于对系统状态对的讨论,提出了判定系统稳定性的有效多项式搜索算法. 相似文献
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个性化推荐是目前解决电子商务中产品信息过载问题的有效工具之一。对综合用户偏好模型和BP神经网络的个性化推荐算法进行了研究。具体讨论了如何建立用户偏好模型,采用神经网络训练得到目标用户的偏好模型,通过Movielens数据库验证该模型的有效性。提出了一个基于内容的个性化推荐算法。 相似文献
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