Abstract. The aim of the given paper is the development of an approach for parametric identifi-cation of Hammerstein systems with piecewise linear nonlinearities, i.e., when the saturation-like function with unknown slopes is followed by a linear part with unknown parameters. It is shown here that by a simple input data rearrangement and by a following data partition the problem of identification of a nonlinear Hammerstein system could be reduced to the linear parametric esti-mation problem. Afterwards, estimates of the unknown parameters of linear regression models are calculated by processing respective particles of input-output data. A technique based on ordinary least squares is proposed here for the estimation of parameters of linear a...
This paper deals with a method for identification of nonlinear systems suitable to be described by H...
Generally, memoryless polynomial nonlinear model for nonlinear part and finite impulse response (FIR...
Hammerstein systems are the series composition of a static nonlinear function and a linear dynamic s...
The aim of the given paper is the development of an approach for parametric identification of Wiener...
International audienceA two-stage parameter identification method is developed for Hammerstein syste...
International audienceA two-stage parameter identification method is developed for Hammerstein syste...
In literature, various linear and nonlinear model structures are defined to identify the systems. Li...
In literature, various linear and nonlinear model structures are defined to identify the systems. Li...
A novel approach is presented for the analysis and design of identification algorithms for Hammerste...
Hammerstein systems are the series composition of a static nonlinear function and a linear dynamic s...
This paper deals with a method for identification of nonlinear systems suitable to be described by H...
Hammerstein systems are the series composition of a static nonlinear function and a linear dynamic s...
Hammerstein systems are the series composition of a static nonlinear function and a linear dynamic s...
Hammerstein systems are the series composition of a static nonlinear function and a linear dynamic s...
Generally, memoryless polynomial nonlinear model for nonlinear part and finite impulse response (FIR...
This paper deals with a method for identification of nonlinear systems suitable to be described by H...
Generally, memoryless polynomial nonlinear model for nonlinear part and finite impulse response (FIR...
Hammerstein systems are the series composition of a static nonlinear function and a linear dynamic s...
The aim of the given paper is the development of an approach for parametric identification of Wiener...
International audienceA two-stage parameter identification method is developed for Hammerstein syste...
International audienceA two-stage parameter identification method is developed for Hammerstein syste...
In literature, various linear and nonlinear model structures are defined to identify the systems. Li...
In literature, various linear and nonlinear model structures are defined to identify the systems. Li...
A novel approach is presented for the analysis and design of identification algorithms for Hammerste...
Hammerstein systems are the series composition of a static nonlinear function and a linear dynamic s...
This paper deals with a method for identification of nonlinear systems suitable to be described by H...
Hammerstein systems are the series composition of a static nonlinear function and a linear dynamic s...
Hammerstein systems are the series composition of a static nonlinear function and a linear dynamic s...
Hammerstein systems are the series composition of a static nonlinear function and a linear dynamic s...
Generally, memoryless polynomial nonlinear model for nonlinear part and finite impulse response (FIR...
This paper deals with a method for identification of nonlinear systems suitable to be described by H...
Generally, memoryless polynomial nonlinear model for nonlinear part and finite impulse response (FIR...
Hammerstein systems are the series composition of a static nonlinear function and a linear dynamic s...