论文标题
脉冲生物医学模型中的输入序列和参数估计
Input Sequence and Parameter Estimation in Impulsive Biomedical Models
论文作者
论文摘要
考虑了一个由二阶线性时间不变的系统组成的生物医学时间序列的混合模型，该模型由一个由阳性加权的Dirac Delta触点的输入序列驱动。研究了输入序列的联合估计和输出测量的连续系统参数的问题。提出了一种基于并完善先前发表的最小二乘配方的解决方案。基于对最小二乘解决方案的性能的透彻分析，与原始算法相比，在合成数据上的准确性和易用性方面得到了改善。
A hybrid model for biomedical time series comprising a continuous second-order linear time-invariant system driven by an input sequence of positively weighted Dirac delta-functions is considered. The problem of the joint estimation of the input sequence and the continuous system parameters from output measurements is investigated. A solution that builds upon and refines a previously published least-squares formulation is proposed. Based on a thorough analysis of the properties of the least-squares solution, improvements in terms of accuracy and ease of use are achieved on synthetic data, compared to the original algorithm.
