论文标题
（随机 - ）延迟方程的模型订单降低具有误差界限
Model Order Reduction for (Stochastic-) Delay Equations With Error Bounds
论文作者
论文摘要
我们根据平衡截断方法分析了一种延迟和随机延迟方程的结构延伸模型降低技术，并提供了系统理论解释。基于Hankel运算符转移误差界限以延迟系统，我们发现了整个模型和还原模型动力学之间差异的错误估计。该分析还产生了具有乘法噪声和非零初始状态的双线性系统和随机系统的新误差界限。
We analyze a structure-preserving model order reduction technique for delay and stochastic delay equations based on the balanced truncation method and provide a system theoretic interpretation. Transferring error bounds based on Hankel operators to delay systems, we find error estimates for the difference between the dynamics of the full and reduced model. This analysis also yields new error bounds for bilinear systems and stochastic systems with multiplicative noise and non-zero initial states.
