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Approximation of the Joint Spectral Radius of a Set of Matrices Using Sum of Squares

机译:使用平方和逼近一组矩阵的联合谱半径

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We provide an asymptotically tight, computationally efficient approximation of the joint spectral radius of a set of matrices using sum of squares (SOS) programming. The approach is based on a search for a SOS polynomial that proves simultaneous contractibility of a finite set of matrices. We provide a bound on the quality of the approximation that unifies several earlier results and is independent of the number of matrices. Additionally, we present a comparison between our approximation scheme and a recent technique due to Blondel and Nesterov, based on lifting of matrices. Theoretical results and numerical investigations show that our approach yields tighter approximations.
机译:我们使用平方和(SOS)编程提供了一组矩阵的联合光谱半径的渐近紧密,计算有效的近似值。该方法基于对SOS多项式的搜索,该多项式可证明有限组矩阵的同时可收缩性。我们提供了近似质量的界线,该界线统一了多个较早的结果,并且与矩阵的数量无关。此外,我们基于矩阵提升提出了近似方案与归功于Blondel和Nesterov的最新技术之间的比较。理论结果和数值研究表明,我们的方法得出了更严格的近似值。

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