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Quasi-finite-rank approximation of compression operators based on L0, h-induced norm

机译:基于L 0,h诱导范数的压缩算子的拟有限秩逼近

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This paper deals with an approximation problem of compression operators, which play important roles in the operator-theoretic approach to sampled-data systems and time-delay systems. More precisely, we study a method for quasi-finite-rank approximation of compression operators in the L[0, h]-induced norm sense. We apply the idea of the Fast-Sample/Fast-Hold (FSFH) approximation technique, and show that the approximation problem can be transformed into such a linear programming problem that asymptotically leads to optimal approximation as the FSFH approximation parameter M tends to infinity. Finally, numerical examples are given to demonstrate the effectiveness of the apprxoimation technique.
机译:本文讨论了压缩算子的一个近似问题,它在样本数据系统和时滞系统的算子理论方法中起着重要的作用。更准确地说,我们研究了一种在L [0,h]引起的范数意义上的压缩算子的准有限秩逼近方法。我们应用了快速采样/快速保持(FSFH)逼近技术的思想,并表明该逼近问题可以转换为这样的线性规划问题,即随着FSFH逼近参数M趋于无穷大,渐近导致最优逼近。最后,通过数值例子说明了逼近技术的有效性。

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