论文标题
递归最小二乘有变化的方向遗忘 - 弥补持久性的损失
Recursive Least Squares with Variable-Direction Forgetting -- Compensating for the loss of persistency
论文作者
论文摘要
学习取决于获取和吸收新信息的能力。这种能力取决于 - 在某种程度上是违反直觉的 - - 忘记的能力。特别是，有效忘记需要识别和利用新信息来命令更新系统模型的能力。本文是关于在递归最小二乘（RLS）背景下忘记的教程。为此，RLS首先以其经典形式呈现，该形式采用了统一的方向遗忘。接下来，举例说明了对可变方向遗忘的需求，尤其是在激发不持续的情况下。其中一些结果是众所周知的，而另一些结果补充了先前的文献。目的是为学生和研究人员提供有关主要思想和技术的独立教程，他们的研究可能会受益于可变方向遗忘。
Learning depends on the ability to acquire and assimilate new information. This ability depends---somewhat counterintuitively---on the ability to forget. In particular, effective forgetting requires the ability to recognize and utilize new information to order to update a system model. This article is a tutorial on forgetting within the context of recursive least squares (RLS). To do this, RLS is first presented in its classical form, which employs uniform-direction forgetting. Next, examples are given to motivate the need for variable-direction forgetting, especially in cases where the excitation is not persistent. Some of these results are well known, whereas others complement the prior literature. The goal is to provide a self-contained tutorial of the main ideas and techniques for students and researchers whose research may benefit from variable-direction forgetting.
