We study the bit complexity of two related fundamental computational problems in linear algebra and control theory. Our results are: (1) An $\tilde{O}(n^{\omega+3}a+n^4a^2+n^\omega\log(1/\epsilon))$ time algorithm for finding an $\epsilon-$approximation to the Jordan Normal form of an integer matrix with $a-$bit entries, where $\omega$ is the exponent of matrix multiplication. (2) An $\tilde{O}(n^6d^6a+n^4d^4a^2+n^3d^3\log(1/\epsilon))$ time algorithm for $\epsilon$-approximately computing the spectral factorization $P(x)=Q^*(x)Q(x)$ of a given monic $n\times n$ rational matrix polynomial of degree $2d$ with $a-$bit coefficients which satisfies $P(x)\succeq 0$ for all real $x$. The first algorithm is used as a subroutine in the second one. Despite its being of central importance, polynomial complexity bounds were not previously known for spectral factorization, and for Jordan form the best previous best boolean running time was an unspecified polynomial of degree at least twelve \cite{cai1994computing}. Our algorithms are simple and judiciously combine techniques from numerical and symbolic computation, yielding significant advantages over either approach by itself.
翻译:我们研究了线性代数和控制理论中两个相关基本计算问题的比重复杂性。 我们的结果是:(1) $\ tilde{O}( n ⁇ omega+3} a+n>4a2+\2+n ⁇ omega\log( 1/\\ epsilon) $( \\ epsilon)) 用于寻找 $\ epsilon- $ a- occol 和 $- bits 的整数矩阵格式的比重。 (2) $\ omga 美元是矩阵乘法乘法乘法乘法。 (2) $\ tilde{O} (n\ d%6a+ n4d_ 4d ⁇ 2+ n3d3\ log\ log(1\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\