发表机构
Department of Mathematics, Shanghai Normal University(上海师范大学数学系)
机构由 AI 辅助整理,请以论文原文为准。AI 中文总结
本文对Sobolev空间上的连续、SL(n)逆变且平移不变的张量赋值进行了完整分类,并证明齐次情形下这些赋值恰为Fisher信息张量,即Fisher信息矩阵的高阶推广。
AI 中文摘要
本文建立了定义在Sobolev空间$W^{1,p}(\mathbb R^n)$上的连续、SL($n$)逆变且平移不变的张量赋值的完整分类。当进一步假设这些赋值为齐次时,分类结果表明它们恰好是Fisher信息张量,后者构成了Fisher信息矩阵的高阶推广。
英文摘要
A complete classification is established for continuous, SL($n$) contravariant, and translation invariant tensor valuations defined on the Sobolev space $W^{1,p}(\mathbb R^n)$. When these valuations are further assumed to be homogeneous, the classification reveals that they are precisely the Fisher information tensors, which constitute a higher-order generalization of the Fisher information matrix.