Statistics

Algorithm

Identification (biology)

System identification

Physics

Mathematical optimization

Mathematical analysis

Estimation theory

Estimator

Parametrization (atmospheric modeling)

Key (lock)

Mathematics

Computer security

Computer science

Botany

Quantum mechanics

Data modeling

Impulse (physics)

Impulse response

Radiative transfer

Database

Biology

Least-squares function approximation

Journal of the Franklin Institute

This paper considers the parameter estimation problems of two-input single-output Hammerstein finite impulse response systems. A hierarchical least squares algorithm is proposed for improving the computational efficiency through combining the hierarchical identification principle and the identification model decomposition, and a multi-innovation least squares algorithm is proposed for enhancing the parameter estimation accuracy based on the multi-innovation identification theory. The key is to derive two sub-identification models, each of which contains a set of merged parameter vectors. The proposed algorithm is effective and can generate highly accurate parameter estimates compared with the over-parametrization identification method, and can be easily extended to multi-input multi-output systems. Finally, an illustrative example is provided to verify the effectiveness of the proposed algorithm.

Hierarchical least squares parameter estimation algorithm for two-input Hammerstein finite impulse response systems