Identification of Wiener systems with binary-valued output observations
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Towards identification of Wiener systems with the least amount of a priori information: IIR cases
Automatica (Journal of IFAC)
Discrete-time quantized H∞ filtering with quantizer ranges consideration
ACC'09 Proceedings of the 2009 conference on American Control Conference
CCDC'09 Proceedings of the 21st annual international conference on Chinese Control and Decision Conference
On identification of FIR systems having quantized output data
Automatica (Journal of IFAC)
Automatica (Journal of IFAC)
Hi-index | 35.69 |
A normalized stochastic gradient adaptive filtering algorithm based on a finite impulse response (FIR) model is discussed. The algorithm identifies the system exactly, given only coarsely quantized output measurements. A description of the quantizer is included in the overall input-output model, and the scheme exploits an approximation of the derivative of the quantizer. Using an associated differential equation, global convergence is established to a zero output error (except for possible colored measurement disturbances) parameter setting or to the boundary of the model set