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Online system identification using matrix pseudoinverse

Online system identification using matrix pseudoinverse

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Recursive algorithms for online identification of discrete-time systems have been described. These provide minimum-norm estimates of the parameter vector when insufficient data are available, and least-squares estimates with sufficient data. Matrix inversion is not required; nor is the a priori knowledge of noise statistics or probability densities of the parameters.

References

    1. 1)
      • A.I. Liff . System identification in the presence of noise by digital techniques. IEEE Internat. Conv. Rec.
    2. 2)
      • A. Albert , R.W. Sittler . A method for computing least squares estimators that keep up with the data. SIAM J. Control , 384 - 417
    3. 3)
      • C.H. Wells . Minimum norm control of discrete systems. IEEE Internat. Conv. Rec. , 55 - 64
    4. 4)
      • F.W. Smith . System Laplace transform estimation from sampled data. IEEE Trans. , 37 - 44
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