TThis paper is devoted to condition numbers of the total least squares problem with linear equality constraint (TLSE). With novel limit techniques, closed formulae for normwise, mixed and componentwise condition numbers of the TLSE problem are derived. Compactexpressionsandupper bounds for these condition numbers are also given to avoid the costly Kronecker product-based operations. Explicit condition number expressions and perturbation bound for the TLS problem can be recovered from our estimates. With TLSE problems solved by the classical QR-SVD or randomized algorithms, numerical experiments illustrate that normwise condition number-based estimate is sharp to evaluate the forward error of the solution, while for sparse and badly scaled matrices, the estimates based on mixed and componentwise condition numbers are much tighter.
翻译:本文专门论述线性平等限制(TLSE)下所有最不平方问题的条件号。 有了新的限值技术, 就可以得出关于TLSE问题规范性、 混合性和 组成部分性条件号的封闭公式。 也给出了这些条件号的压缩表达式和调试框, 以避免昂贵的Kronecker产品操作。 从我们的估算中可以找到与 TLS 问题相关的明确条件号表达式和扰动性。 由于传统QR- SVD 或随机算法解决了 TLSE 问题, 数字实验表明, 以标准性条件号为基础的估计对于评估解决方案的远端错误来说是敏锐的, 而对于稀疏和比例极差的矩阵, 以混合和组成部分性条件号为基础的估计则更加紧凑。