Complex-Valued Best Linear Unbiased Estimator of an Unknown Constant Mean of White Noise

TL;DR

This paper derives a complex-valued best linear unbiased estimator for the unknown mean of white noise, extending traditional methods to complex domain, and compares it with the ordinary least-squares estimator.

Contribution

It introduces a novel complex-valued estimator for the mean of white noise, providing a new approach to unbiased estimation in complex settings.

Findings

The complex-valued estimator is unbiased and efficient.

Comparison shows advantages over traditional least-squares in certain conditions.

The method extends classical estimation theory to complex-valued data.

Abstract

In this paper the complex-valued best linear unbiased estimator of an unknown constant mean of white noise was derived the ordinary least-squares estimator of an unknown constant mean of random field (arithmetic mean) charged by an imaginary error.