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On the error exponents for detecting randomly sampled noisy diffusion processes

机译:用于检测随机采样的噪声扩散过程的误差指数

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This paper deals with the detection of a continuous random process described by an Ornstein-Uhlenbeck (O-U) stochastic differential equation. Randomly spaced sensors or equivalently a random time sampler which deliver noisy samples of the process are used for this detection. Two types of tests are considered: either H0 refers to the presence of the noisy O-U process or H0 refers to the sole presence of noise. For any fixed false alarm probability, it is shown that the type II error probability decreases to zero exponentially in the number of samples. The exponents, which do not depend on the false alarm probability, are characterized. This work completes former contributions that consider noiseless O-U process with a random sampling or noisy O-U processes with a regular sampling.
机译:本文讨论了由Ornstein-Uhlenbeck(O-U)随机微分方程描述的连续随机过程的检测。这种检测使用了随机分布的传感器或等效的随机时间采样器,该采样器会传递过程的噪声样本。考虑了两种类型的测试:H0表示存在噪声的O-U过程,或者H0表示仅存在噪声。对于任何固定的虚警概率,表明II类错误概率在样本数量中呈指数下降为零。表征不依赖于虚警概率的指数。这项工作完成了以前的考虑,即考虑采用随机采样的无噪声O-U过程或采用常规采样的嘈杂的O-U过程。

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