Eigenspace-Based Clustering for Personalized System Identification
The method proposes a one-shot, training-free approach to cluster heterogeneous linear systems based on shared underlying dynamics. It avoids iterative training by measuring alignment between systems' covariance eigenspaces to group them for collaborative model training, achieving lower identification errors than traditional methods.