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Optimal linear-quadratic systems for detection and estimation

机译:用于检测和估计的最佳线性二次系统

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摘要

The problem of linear-quadratic systems for detection has long been solved by assuming the deflection criterion and Gaussian noise. It is shown here that the Gaussian assumption can be removed, and a complete solution is presented for an arbitrary probability distribution with finite fourth-order moments. The optimal solution can always be obtained by solving a linear system of equations. Some properties of the optimal systems are developed for particular examples of nonGaussian noise. It is shown that there is a strong relationship between linear-quadratic optimal detection and optimal estimation, which extends results known for the purely linear case.
机译:长期以来,通过采用偏转准则和高斯噪声解决了线性二次系统的检测问题。此处显示出可以消除高斯假设,并且给出了具有有限四阶矩的任意概率分布的完整解。最佳解总是可以通过求解线性方程组来获得。针对非高斯噪声的特定示例,开发了最佳系统的某些属性。结果表明,线性二次最优检测与最优估计之间存在很强的关系,这扩展了纯线性情况下已知的结果。

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