A 1/R Law for Kurtosis Contrast in Balanced Mixtures

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Authors: Yuda Bi, Wenjun Xiao, LinHao Bai, Vince D Calhoun
Cited by: 0

Abstract

Kurtosis-based Independent Component Analysis (ICA) weakens in wide, balanced mixtures. We prove a sharp redundancy law: for a standardized projection with effective width $R_{\mathrm{eff}}$ (participation ratio), the population excess kurtosis obeys $|κ(y)|=O(κ_{\max}/R_{\mathrm{eff}})$, yielding the order-tight $O(c_bκ_{\max}/R)$ under balance (typically $c_b=O(\log R)$). As an impossibility screen, under standard finite-moment conditions for sample kurtosis estimation, surpassing the $O(1/\sqrt{T})$ estimation scale requires $R\lesssim κ_{\max}\sqrt{T}$. We also show that \emph{purification} -- selecting $m\!\ll\!R$ sign-consistent sources -- restores $R$-independent contrast $Ω(1/m)$, with a simple data-driven heuristic. Synthetic experiments validate the predicted decay, the $\sqrt{T}$ crossover, and contrast recovery.

Fields of Study & Subjects

Blind Source Separation Techniques Tensor decomposition and applications Statistical Methods and Applications

Publication details

Journal / source
IEEE Signal Processing Letters
Volume
33
Pages
4181–4185
Publication date
1 January 2026
Language
EN