System identification: theory for the user
System identification: theory for the user
Automatica (Journal of IFAC)
Adaptive filtering with binary reinforcement
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
A note on convergence under dynamical thresholds with delays
IEEE Transactions on Neural Networks
Asymptotically efficient parameter estimation using quantized output observations
Automatica (Journal of IFAC)
Identification of Wiener systems with binary-valued output observations
Automatica (Journal of IFAC)
Space and time complexities and sensor threshold selection in quantized identification
Automatica (Journal of IFAC)
Tracking and identification of regime-switching systems using binary sensors
Automatica (Journal of IFAC)
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
Identification of Hammerstein Systems with Quantized Observations
SIAM Journal on Control and Optimization
Automatica (Journal of IFAC)
Hi-index | 22.15 |
System identification of plants with binary-valued output observations is of importance in understanding modeling capability and limitations for systems with limited sensor information, establishing relationships between communication resource limitations and identification complexity, and studying sensor networks. This paper resolves two issues arising in such system identification problems. First, regression structures for identifying a rational model contain non-smooth nonlinearities, leading to a difficult nonlinear filtering problem. By introducing a two-step identification procedure that employs periodic signals, empirical measures, and identifiability features, rational models can be identified without resorting to complicated nonlinear searching algorithms. Second, by formulating a joint identification problem, we are able to accommodate scenarios in which noise distribution functions are unknown. Convergence of parameter estimates is established. Recursive algorithms for joint identification and their key properties are further developed.