Identification of Wiener Model with Internal Noise Using a Cubic Spline Approximation-Bayesian Composite Quantile Regression Algorithm
A cubic spline approximation-Bayesian composite quantile regression algorithm is proposed to estimate parameters and structure of the Wiener model with internal noise. Firstly, an ARX model with a high order is taken to represent the linear block; meanwhile, the nonlinear block (reversibility) is ap...
Saved in:
| Main Authors: | Tianhong Pan, Wei Guo, Ying Song, Fujia Yin |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/9195819 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Natural Cubic Spline Approximation of Risk-Neutral Density
by: Shuang Zhou, et al.
Published: (2024-12-01) -
COMPARISON BETWEEN BAYESIAN QUANTILE REGRESSION AND BAYESIAN LASSO QUANTILE REGRESSION FOR MODELING POVERTY LINE WITH PRESENCE OF HETEROSCEDASTICITY IN WEST SUMATRA
by: Lilis Harianti Hasibuan, et al.
Published: (2025-07-01) -
Approximation Analysis of Learning Algorithms for Support Vector Regression and Quantile Regression
by: Dao-Hong Xiang, et al.
Published: (2012-01-01) -
The Principal Component Linear Spline Quantile Regression Model in Statistical Downscaling for Rainfall Data
by: Andi Yulianti, et al.
Published: (2024-04-01) -
An optimized cubic B-spline algorithm for high-precision approximation of nonlinear transport phenomena
by: Rabia Noureen, et al.
Published: (2025-09-01)