Control Systems and Identification

Practical Identifiability of a Minimal Adaptive Learning-Gain Model for Binary Feedback: A Simulation Study

This paper evaluates the practical identifiability of a four-parameter adaptive learning-gain model for binary feedback through simulations, finding poor parameter recovery and no predictive advantage over a baseline.

Beyond the attractor: closed-loop stimulation design for learning multistable neural dynamics

This paper introduces PALDI, a method for active closed-loop stimulation to identify neural dynamics, showing improved performance in noisy and biased observation scenarios.