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A robust minimum-variance filter for time varying uncertain discrete-time systems

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Computing the equivalent number of parameters of fixed-interval smoothers

Giancarlo Ferrari Trecate

The problem of reconstructing an unknown signal from

n

noisy samples can be addressed by means of nonparametric estimation techniques such as Tikhonov regularization, Bayesian regression and state-space fixed-interval smoothing. The practical use of thes ...

2001

A robust minimum-variance filter for time varying uncertain discrete-time systems

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Chat with Graph Search

The analysis of kernel ridge regression learning algorithm.

Computing the equivalent number of parameters of fixed-interval smoothers

A time-domain feedback analysis of filtered-error adaptive gradient algorithms

A time-domain feedback analysis of filtered-error adaptive gradient algorithms

The analysis of kernel ridge regression learning algorithm.

Computing the equivalent number of parameters of fixed-interval smoothers