论文标题
使用随机预测部分自适应过滤
Partially adaptive filtering using randomized projections
论文作者
论文摘要
此简短说明介绍了部分自适应滤波器的设计，以检索存在强烈的低级干扰和热噪声的信号。我们考虑了一个广义的Sidelobe取消实现，其中减少尺寸的转换构建为从随机矩阵近似值借用的想法。更确切地说，辅助数据$ z $的主要子空间约为$zΩ$，其中$ω$是随机矩阵或以$ z $的随机列选择的矩阵。这些转换不需要特征值分解，但是它们提供的性能类似于主成分滤波器的性能。
This short note addresses the design of a partially adaptive filter to retrieve a signal of interest in the presence of strong low-rank interference and thermal noise. We consider a generalized sidelobe canceler implementation where the dimension-reducing transformation is build resorting to ideas borrowed from randomized matrix approximations. More precisely, the main subspace of the auxiliary data $Z$ is approximated by $ZΩ$ where $Ω$ is a random matrix or a matrix that picks at random columns of $Z$. These transformations do not require eigenvalue decomposition, yet they provide performance similar to those of a principal component filter.
