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Linear systems identification from random threshold binary data

机译:从随机阈值二进制数据识别线性系统

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A new identification problem of estimating parameters of linear dynamic systems from random threshold binary observations of its output and input is stated. The only available data are collected as a result of checking whether a signal reached a randomly specified threshold at a randomly chosen instant of time. The proposed estimation algorithm is based on the celebrated von Neumann theorem, which was earlier used mainly for generating random numbers. Strong consistency of parameters estimate from low-cost output binary observations is proved, assuming deterministic input signal of a finite duration. Possibilities of relaxing the assumption used in the theoretical part of the paper are considered by means of simulations.
机译:提出了一个新的识别问题,即从其输出和输入的随机阈值二进制观测值估计线性动态系统的参数。收集唯一可用的数据是在随机选择的时刻检查信号是否达到随机指定的阈值的结果。所提出的估计算法基于著名的冯·诺依曼定理,该定理先前主要用于生成随机数。假设在有限持续时间内确定输入信号,证明了从低成本输出二进制观测值估计的参数具有很强的一致性。通过模拟考虑了放宽本文理论部分所用假设的可能性。

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