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Discrete smoothing splines and digital filtration. Theory and applications. (English) Zbl 0704.65005
The paper deals with theoretical and applied aspects of discrete smoothing splines and digital filtration. Its aim is to prove the close interconnection between two smoothing approaches, to develop the transfer function which characterizes the smoothing spline as a filter in terms of $$\alpha$$ and $$\lambda_ K$$ (the eigenvalues of the discrete analogue of $${\mathcal L})$$, and to develop the reduction ratio between the original and smoothed data in the same terms. $$(\alpha >0$$ is the smoothing parameter and $${\mathcal L}:$$ $$W^{2,\nu}\to L_ 2$$ is a linear bounded operator). Five physical examples are discussed (sinusoidal wave, saw-like waves, rectangular pulse train, etc.)
Reviewer: M.Gaşpar (Iaşi)

##### MSC:
 65D10 Numerical smoothing, curve fitting 65K10 Numerical optimization and variational techniques 41A15 Spline approximation 65D07 Numerical computation using splines 93E11 Filtering in stochastic control theory 93E14 Data smoothing in stochastic control theory
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