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The Young-Householder algorithm and the least squares multidimensional scaling of squared distances

✍ Scribed by M. W. Browne

Publisher
Springer
Year
1987
Tongue
English
Weight
773 KB
Volume
4
Category
Article
ISSN
0176-4268

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In this paper, we provide a ~-norm lower bound on the worst-case identification error of least-squares estimation when using FIR model structures. This bound increases as a logarithmic function of model complexity and is valid for a wide class of inputs characterized as being quasi-stationary with c