Sparse kernel regression modeling using combined locally regularized orthogonal least squares and d-optimality experimental design
نویسندگان
چکیده
منابع مشابه
Sparse kernel regression modeling using combined locally regularized orthogonal least squares and D-optimality experimental design
The note proposes an efficient nonlinear identification algorithm by combining a locally regularized orthogonal least squares (LROLS) model selection with a D-optimality experimental design. The proposed algorithm aims to achieve maximized model robustness and sparsity via two effective and complementary approaches. The LROLS method alone is capable of producing a very parsimonious model with e...
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ژورنال
عنوان ژورنال: IEEE Transactions on Automatic Control
سال: 2003
ISSN: 0018-9286
DOI: 10.1109/tac.2003.812790