This report investigates the extension of the Bayesian Subspace System Identification method proposed in our previous work to the Multiple-Input Multiple-Output (MIMO) case. We derive new equivariant priors and posterior distributions specifically suited for the MIMO framework. Numerical results utilizing the DAISY dataset are reported to validate the approach.

翻译：本报告研究了将我们先前工作中提出的贝叶斯子空间系统辨识方法扩展至多输入多输出（MIMO）情形。我们推导了专门适用于MIMO框架的新等变先验分布与后验分布。通过使用DAISY数据集的数值实验结果验证了该方法的有效性。