Locally optimum detection of discrete-time stochastic signals in non-Gaussian noise

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Abstract
Two basic models are considered for the problem of detecting small, zero‐mean stochastic signals in non‐Gaussian noise processes. Appying the theory of local tests, a general detector structure is derived for each of these models. A third (suboptimal) scheme based on null‐zone detection is also proposed and a technique for optimizing its parameters is discussed. Using the criterion of asymptotic relative efficiency, the performance of these three detectors and of a power detector are compared under each of the proposed models.

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