标题： 稳定模型的识别通过非参数预测误差方法 显示英文标题

标题： Identification of stable models via nonparametric prediction error methods

摘要： 一系列近期的论文提出了一种线性系统辨识的新贝叶斯方法。这种方法的主要思想是在无穷维空间中将线性系统辨识问题转化为预测器估计问题，并借助正则化/贝叶斯技术实现。该方法保证了基于预测误差最小化的稳定预测器的辨识。不幸的是，预测器的稳定性并不能保证系统冲激响应的稳定性。本文提出了几种解决这一问题的技术并进行了比较。还将提供这些技术的仿真结果进行对比。 显示英文摘要

摘要： A new Bayesian approach to linear system identification has been proposed in a series of recent papers. The main idea is to frame linear system identification as predictor estimation in an infinite dimensional space, with the aid of regularization/Bayesian techniques. This approach guarantees the identification of stable predictors based on the prediction error minimization. Unluckily, the stability of the predictors does not guarantee the stability of the impulse response of the system. In this paper we propose and compare various techniques to address this issue. Simulations results comparing these techniques will be provided.