scholarly journals Regularized nonparametric Volterra kernel estimation

Automatica ◽  
2017 ◽  
Vol 82 ◽  
pp. 324-327 ◽  
Author(s):  
Georgios Birpoutsoukis ◽  
Anna Marconato ◽  
John Lataire ◽  
Johan Schoukens
Keyword(s):  
Kernel Estimation ◽  
Volterra Kernel

Volterra kernel estimation for mildly nonlinear amplifiers

1993 ◽  
Vol 29 (23) ◽  
pp. 2007 ◽  
Author(s):  
J.G. McRory ◽  
R. Johnston
Keyword(s):  
Kernel Estimation ◽  
Volterra Kernel ◽  
Nonlinear Amplifiers

Factors Affecting Volterra Kernel Estimation: Emphasis on Lung Tissue Viscoelasticity

10.1114/1.82 ◽  
1998 ◽  
Vol 26 (1) ◽  
pp. 103-116 ◽  
Author(s):  
Qin Zhang ◽  
Béla Suki ◽  
David T. Westwick ◽  
Kenneth R. Lutchen
Keyword(s):  
Lung Tissue ◽  
Kernel Estimation ◽  
Volterra Kernel ◽  
Factors Affecting

EM-Based Hyperparameter Optimization for Regularized Volterra Kernel Estimation

2017 ◽  
Vol 1 (2) ◽  
pp. 388-393 ◽  
Author(s):  
Jeremy G. Stoddard ◽  
James S. Welsh ◽  
Hakan Hjalmarsson
Keyword(s):  
Kernel Estimation ◽  
Volterra Kernel ◽  
Hyperparameter Optimization

scholarly journals Frequency Domain Kernel Estimation for 2nd-order Volterra Models Using Random Multi-tone Excitation

VLSI Design ◽  
2002 ◽  
Vol 15 (4) ◽  
pp. 701-713 ◽  
Author(s):  
G. Bicken ◽  
G. F. Carey ◽  
R. O. Stearman
Keyword(s):  
Frequency Domain ◽  
Semiconductor Device ◽  
Kernel Estimation ◽  
Harmonic Excitation ◽  
Volterra Kernel ◽  
Volterra Models ◽  
Output System ◽  
Gaussian Input ◽  
Kernel Estimations ◽  
Least Squares Minimization

We consider the problem of frequency domain kernel estimation using random multi-tone (harmonic) excitation for 2nd-order Volterra models. The basic approach is based on least squares minimization of model output error, and results for the Volterra kernel estimations with random multi-tone inputs and random Gaussian input are compared. We show that kernel estimation with multi-tones are very accurate and efficient compared to the latter. As an illustration, the proposed method is applied to a discrete input–output system obtained from the numerical simulation of a representative hydrodynamic system for modeling semiconductor device transport. We also consider the effect of noise in the kernel estimation.

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