Polynomial Complexity of Inversion of sequences and Local Inversion of Maps

Virendra Sule
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Abstract

This Paper defines and explores solution to the problem of \emph{Inversion of a finite Sequence} over the binary field, that of finding a prefix element of the sequence which confirms with a \emph{Recurrence Relation} (RR) rule defined by a polynomial and satisfied by the sequence. The minimum number of variables (order) in a polynomial of a fixed degree defining RRs is termed as the \emph{Polynomial Complexity} of the sequence at that degree, while the minimum number of variables of such polynomials at a fixed degree which also result in a unique prefix to the sequence and maximum rank of the matrix of evaluation of its monomials, is called \emph{Polynomial Complexity of Inversion} at the chosen degree. Solutions of this problems discovers solutions to the problem of \emph{Local Inversion} of a map $F:\ftwo^n\rightarrow\ftwo^n$ at a point $y$ in $\ftwo^n$, that of solving for $x$ in $\ftwo^n$ from the equation $y=F(x)$. Local inversion of maps has important applications which provide value to this theory. In previous work it was shown that minimal order \emph{Linear Recurrence Relations} (LRR) satisfied by the sequence known as the \emph{Linear Complexity} (LC) of the sequence, gives a unique solution to the inversion when the sequence is a part of a periodic sequence. This paper explores extension of this theory for solving the inversion problem by considering \emph{Non-linear Recurrence Relations} defined by a polynomials of a fixed degree $>1$ and satisfied by the sequence. The minimal order of polynomials satisfied by a sequence is well known as non-linear complexity (defining a Feedback Shift Register of smallest order which determines the sequences by RRs) and called as \emph{Maximal Order Complexity} (MOC) of the sequence. However unlike the LC there is no unique polynomial recurrence relation at any degree.
序列反转和地图局部反转的多项式复杂性
本文定义并探讨了二元域上有限序列的反演问题,即寻找序列的前缀元素,该前缀元素与由多项式定义并满足序列的反演关系(RR)规则相一致。定义 RR 的固定阶数的多项式中变量(阶)的最小数目被称为该阶数下序列的 \emph{Polynomial Complexity} (多项式复杂性),而这种多项式在固定阶数下的变量最小数目,也会导致序列的唯一前缀和其单项式求值矩阵的最大秩,被称为所选阶数下的\emph{Polynomial Complexity of Inversion} (多项式反转复杂性)。这个问题的解发现了映射 $F:\ftwo^n\rightarrow\ftwo^n$ 在 $ftwo^n$ 中的点 $y$ 的局部反演问题的解,即从方程 $y=F(x)$ 求解 $ftwo^n$ 中的 $x$。在以前的工作中,有研究表明,当序列是周期序列的一部分时,序列所满足的最小阶[线性递归关系](LRR)即序列的[线性复杂性](LC)给出了唯一的反转解。本文通过考虑由固定阶数 $>1$ 的多项式定义并由序列满足的 \emph{非线性递推关系},探索了解决反演问题的这一理论的扩展。序列满足的多项式的最小阶数是众所周知的非线性复杂度(定义了一个最小阶数的反馈移位寄存器,该寄存器由 RRs 决定序列),被称为序列的 \emph{最大阶数复杂度}(MOC)。然而,与 LC 不同的是,在任何阶数上都没有唯一的多项式递推关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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