The Spectrum of Asymmetry: Why Singular Values Tell the Truth (and Vectors Lie)
中文摘要
奇异值揭示系统增益，特征值则可能欺骗，SVD与特征值分解统一模型。
English Summary
This article compares SVD and eigendecomposition, proposing that singular values represent a system's true invariant gain, whereas eigenvalues can be misleading.
Original Excerpt
A unified mental model of SVD vs eigendecomposition: singular values are the invariant “gain” of a system, while eigenvalues are the… Continue reading on Medium »