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A Stable Dual Purpose Adaptive Algorithm for Subspace Tracking on Noncompact Stiefel Manifold

机译:非紧凑Stiefel流形上子空间跟踪的稳定双用途自适应算法

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Starting from an extended Rayleigh quotient defined on the noncompact Stiefel manifold, in this paper, we present a novel dual purpose subspace flows for subspace tracking. The proposed algorithm can switch from principal subspace to minor subspace tracking with a simple sign change of its stepsize parameter. More interestingly, the proposed dual purpose gradient system behaves the same invariant property as that of the well-known Chen-Amari-Lin system. The stability of the discrete version of the proposed subspace flow is guaranteed by an additional added stabilizing term. No tunable parameter is required for the proposed algorithm as opposed to the modified Oja algorithm. The strengths of the proposed algorithm is demonstrated using a de facto benchmark example.
机译:从在非紧致Stiefel流形上定义的扩展瑞利商开始,在本文中,我们提出了一种用于子空间跟踪的新颖的双重用途子空间流。所提出的算法可以通过对其步长参数进行简单的符号更改来从主要子空间切换到次要子空间跟踪。更有趣的是,所提出的双重目的梯度系统具有与众所周知的Chen-Amari-Lin系统相同的不变性。所建议的子空间流的离散版本的稳定性通过附加的稳定项来保证。与改进的Oja算法相反,该算法不需要可调参数。使用一个实际的基准示例证明了所提出算法的优势。

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