论文标题
关于随机过程的跟踪性
On the Trackability of Stochastic Processes
论文作者
论文摘要
我们考虑通过使用另一个随机过程$ y_t $的因果知识来跟踪不稳定随机过程$ x_t $的问题。我们获得了维持有限跟踪误差的必要条件和足够条件。我们提供了必要的条件以及足够的条件，以实现此估计的成功，该估计定义为$ M $ MONM MONSTAIMION。这项研究的副产品是统计数据之间的联系，例如Rényi熵，Gallager的可靠性功能和任何时间容量的概念。
We consider the problem of tracking an unstable stochastic process $X_t$ by using causal knowledge of another stochastic process $Y_t$. We obtain necessary conditions and sufficient conditions for maintaining a finite tracking error. We provide necessary conditions as well as sufficient conditions for the success of this estimation, which is defined as order $m$ moment trackability. By-products of this study are connections between statistics such as Rényi entropy, Gallager's reliability function, and the concept of anytime capacity.
