论文标题
LMS算法的统计分析，用于适当和不当的高斯过程
Statistical Analysis of the LMS Algorithm for Proper and Improper Gaussian Processes
论文作者
论文摘要
LMS算法是自适应滤波中使用最广泛的技术之一。在各种情况下，算法的准确建模对于实现有效的自适应维也纳滤波器设计过程至关重要。在最近几十年中，人们对研究不正确的信号并为正确和不当信号提供了准确的LMS算法模型引起了人们的关注。 LMS算法的其他模型在科学文献中可用的信号不当，要么利用有关所需信号和输入信号向量的独立性假设，要么是适当的信号；结果表明，通过不考虑这些假设，可以得出更一般的模型。在介绍的模拟中，可以验证本文中引入的模型是否优于其他可用模型。
The LMS algorithm is one of the most widely used techniques in adaptive filtering. Accurate modeling of the algorithm in various circumstances is paramount to achieving an efficient adaptive Wiener filter design process. In the recent decades, concerns have been raised on studying improper signals and providing an accurate model of the LMS algorithm for both proper and improper signals. Other models for the LMS algorithm for improper signals available in the scientific literature either make use of the independence assumptions regarding the desired signal and the input signal vector, or are exclusive to proper signals; it is shown that by not considering these assumptions a more general model can be derived. In the presented simulations it is possible to verify that the model introduced in this paper outperforms the other available models.
