Abstract
Conditions on input signals are derived that characterize their probing richness for system identification using binary-valued observations. Identification configurations in open-loop, filtering, and feedback systems are discussed together with different scenarios of noises including actuator noise, input measurement noise, and output measurement noises. In addition to system parameter estimation, identifiability and sufficient excitation conditions are also derived under unknown threshold and noise distributions.
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