The difficult term in the condition number $\| A\n \, \| A^{-1}\|$ of a large linear system $Ap=y$ is the spectral norm of $A^{-1}$. To eliminate this term, we here replace worst case analysis by a probabilistic argument. To be more precise, we randomly take $p$ from a ball with the uniform distribution and show that then, with a certain probability close to one, the relative errors $\| \de p\|$ and $\| \de y\|$ satisfy $\| \delta p\| \le C \| \delta y\|$ with a constant $C$ that involves only the Frobenius and spectral norms of $A$. The success of this argument is demonstrated for Toeplitz systems and for the problem of sampling multivariate trigonometric polynomials on nonuniform
knots. The limitations of the argument are also shown.
Keywords:
condition number, probability argument, linear system, Toeplitz matrix, nonuniform sampling,
multivariate trigonometric polynomial