Recursive least squares estimation methods for a class of nonlinear systems based on non‐uniform sampling

2021 ◽  
Author(s):  
Qilin Liu ◽  
Feiyan Chen ◽  
Feng Ding ◽  
Ahmed Alsaedi ◽  
Tasawar Hayat
Keyword(s):  
Nonlinear Systems ◽  
Least Squares ◽  
Least Squares Estimation ◽  
Recursive Least Squares ◽  
Estimation Methods ◽  
Uniform Sampling ◽  
Non Uniform Sampling

SYSTOLIC ALGORITHMS FOR RECURSIVE TOTAL LEAST SQUARES PARAMETER ESTIMATION AND MIXED RLS/RTLS PROBLEMS

1993 ◽  
Vol 04 (01) ◽  
pp. 55-68 ◽  
Author(s):  
MARC MOONEN
Keyword(s):  
Parameter Estimation ◽  
Least Squares ◽  
Total Least Squares ◽  
Parallel Architectures ◽  
Least Squares Estimation ◽  
Recursive Least Squares ◽  
Recursive Algorithms ◽  
Least Squares Problems ◽  
Linearly Constrained ◽  
Systolic Algorithms

Total least squares parameter estimation is an alternative to least squares estimation though much less used in practice, partly due to the absence of efficient recursive algorithms or parallel architectures. Here it is shown how previously developed systolic algorithms/architectures for recursive least squares estimation can be used for recursive total least squares problems. Unconstrained as well as linearly constrained and "mixed RLS/RTLS" problems are considered.

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