Exact(19)
These approximation techniques are exploited to the design of the derivative-free smoothers and predictors.
These approximation ratios greatly improve over the best (known) deterministic incentive-compatible mechanisms for these classes.
These approximation algorithms outperform the existing state-of-the-art methods.
These approximation and assumption would lead to the inevitable error in the calculation of inverse matrix especially in higher time-varying fading channels.
These approximation are derived using a ratio of correlated Gaussians approach.
The problems that arise while using these approximation methods are discussed here.
Similar(41)
In what follows, many of the relationships are held only approximately, but because these approximations are often very good we show them as equalities.
This effectiveness depends on how precisely the raw data can be approximated and how precisely these approximations can be compared.
However, they do not allow quantum mechanics to "approximately reduce" chemical facts, because the errors introduced by these approximations cannot be estimated (Scerri, 1991, 1994).
Recurrence relations describe the time evolution of these approximations.
Several modifications of these approximations are presented.
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