Optimal quantization of signals for system identification
Optimal quantization of signals for system identification
复制标题
用于系统识别的信号的最佳量化
DOI：
10.23919/ecc.2003.7085053
复制
发表时间：
2003
期刊：
影响因子：
--
通讯作者：
Jan M. Maciejowski
中科院分区：
文献类型：
--
作者：
K. Tsumura;Jan M. Maciejowski
在本文中，我们分析了用于系统识别的信号量化的效果，并给出了在量化信号的子段数约束下最小化估计误差的最优量化方案。最优量化方案在信号的定义区域内，在原点附近是粗的，在离原点较远的地方是密的。我们还评估了估计的参数，并在输出数据信息量的约束下显示了量化误差和噪声误差之间的权衡。
In this paper, we analyse the effect of the quantization of signals used for system identification and show an optimal quantization scheme for minimizing estimation errors under a constraint on the number of subsections of the quantized signals. The optimal quantization scheme has the property that it is coarse near the origin and dense at a distance from it in the definition area of the signals. We also evaluate the estimated parameters and show a trade-off between the quantization error and the noise error under the constraint on the amount of information in the output data.