System identification with generalized orthonormal basis functions
Automatica (Journal of IFAC) - Special issue on trends in system identification
Adaptive modelling, estimation and fusion from data: a neurofuzzy approach
Adaptive modelling, estimation and fusion from data: a neurofuzzy approach
Automatica (Journal of IFAC)
A frequency-domain iterative identification algorithm using general orthonormal basis functions
Automatica (Journal of IFAC)
Nonlinear system identification via direct weight optimization
Automatica (Journal of IFAC)
Regressor selection with the analysis of variance method
Automatica (Journal of IFAC)
Identification of nonlinear additive FIR systems
Automatica (Journal of IFAC)
Using wavelet network in nonparametric estimation
IEEE Transactions on Neural Networks
Hi-index | 22.14 |
In this paper, we propose a new representation which is particularly useful for a class of non-parametric nonlinear systems that have short term memory and low degree of interaction. Advantages and disadvantages of this representation are discussed and compared to existing methods both theoretically and numerically. Furthermore, results regarding structural estimation based on the analysis of variance and on full scale identification are also provided.