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SIAMCO
2010

Identification of Hammerstein Systems with Quantized Observations

11 years 6 months ago
Identification of Hammerstein Systems with Quantized Observations
This work is concerned with identification of Hammerstein systems whose outputs are measured by quantized sensors. The system consists of a memoryless nonlinearity that is polynomial and possibly noninvertible, followed by a linear subsystem. The parameters of linear and nonlinear parts are unknown but have known orders. Input design, identification algorithms, and their essential properties are presented under the assumptions that the distribution function of the noise is known and the quantization thresholds are known. The concept of strongly scaled full rank signals is introduced to capture the essential conditions under which the Hammerstein system can be identified with set-valued observations. Under strongly scaled full rank conditions, a strongly convergent algorithm is constructed. Asymptotic consistency and efficiency of the algorithm are investigated. Key words. identification, quantized observations, Hammerstein systems, parameter estimation, quantization thresholds, strongl...
Yanlong Zhao, Ji-Feng Zhang, Le Yi Wang, Gang Geor
Added 21 May 2011
Updated 21 May 2011
Type Journal
Year 2010
Where SIAMCO
Authors Yanlong Zhao, Ji-Feng Zhang, Le Yi Wang, Gang George Yin
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