On the Use of Regularization in System Identification

@inproceedings{McKelveyDepartment1992OnTU,
  title={On the Use of Regularization in System Identification},
  author={T. McKelveyDepartment},
  year={1992}
}
  • T. McKelveyDepartment
  • Published 1992
Regularization is a standard statistical technique to deal with ill-conditioned parameter estimation problems. We discuss in this contribution what possibilities and advantages regularization ooers in system identiication. In the rst place regularization reduces the variance error of a model, but at the same time it introduces a bias. The familiar trade-oo between bias and variance error for the choice of model order/structure can therefore be discussed in terms of the regularization parameter… CONTINUE READING

References

Publications referenced by this paper.
Showing 1-3 of 3 references

Fleming . Equivalence of regularization and truncated iteration inthe solution of ill - posed image reconstruction problems

  • M. Heath, G. Wahba
  • Linear Algebra andits Applications
  • 1990

\ Generalized Cross - Validation as aMethod for Choosing a Good Ridge Parameter "

  • Chong Gu
  • Technometrics
  • 1979

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