|国家预印本平台
首页|Information Retention in Iterative Random Projection of Convex Bodies to Lower Dimensions

Information Retention in Iterative Random Projection of Convex Bodies to Lower Dimensions

Information Retention in Iterative Random Projection of Convex Bodies to Lower Dimensions

来源:Arxiv_logoArxiv
英文摘要

In this paper, we consider a bounded convex body $K_0 \subset \mathbb{R}^{n}$ subjected to two successive random orthogonal projections onto $\mathbb{R}^{n-1}$ and $\mathbb{R}^{n-2}$, respectively. First, we project $K_0$ orthogonally onto $U_{1}^{\perp}$, the orthogonal complement of $\mbox{\boldmath $U$}_1$, where $\mbox{\boldmath $U$}_1$ is uniformly distributed on the unit sphere $S^{n-1}$. This yields a random convex body $K_1 = \mathrm{Proj}_{{U_1}^{\perp}}(K_0) \subset \mathbb{R}^{n-1}$. We then repeat the process, projecting $K_1$ orthogonally onto ${U}_{2}^{\perp}$, the orthogonal complement of $\mbox{\boldmath $U$}_2$ chosen uniformly from the unit sphere in $\mbox{\boldmath $U$}_{1}^{\perp}$ or $S^{n-2}$, resulting in a second random convex body $K_2 = \mathrm{Proj}_{{U_2}^{\perp}}(K_1) \subset \mathbb{R}^{n-2}$. To quantify information retention through these sequential dimension reductions, we derive an upper bound for the conditional mutual information $I(K_1;K_2 \mid K_0)$. Furthermore, we extend this process to $m$ iterations and generalize the upper bound on $I(K_1;K_2 \mid K_0)$ to establish an analogous upper bound for $I(K_1;K_m \mid K_0)$. Finally, we examine the influence of $K_0$'s symmetry on the achievability of this upper bound for $I(K_1;K_m \mid K_0)$.

Nazanin Mirhosseini

数学

Nazanin Mirhosseini.Information Retention in Iterative Random Projection of Convex Bodies to Lower Dimensions[EB/OL].(2025-08-13)[2025-08-24].https://arxiv.org/abs/2508.10218.点此复制

评论