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Determines structure through diffraction effects: the phase problem, Patterson function, and direct methods for phase determination.
Existing methods for phase estimation in physiological signals often suffer from a lack of thorough description and standardization, which renders reproducibility and interpretation difficult.
Since formal statistical methods for phase I and II trials have been mostly developed for cancer drugs, a considerable portion of this chapter addresses statistical issues in this particular setting.
This paper explored the use of Monte Carlo methods for phase noise estimation.
This paper investigates the use of Monte Carlo sampling methods for phase noise estimation on additive white Gaussian noise (AWGN) channels.
See Table 1 for outcome measures and testing methods for phase 1.
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We propose new collocation methods for phase-field models.
We introduce provably unconditionally stable mixed variational methods for phase-field models.
These attributes permitted us to derive accurate, efficient, and geometrically flexible collocation methods for phase-field models.
Analysis methods for phase-encoded data were similar to previous studies (Sereno et al. 1995; Tootell et al. 1997; Hagler and Sereno 2006; Pitzalis et al. 2006).
There are three basic methods for phasing: molecular, genetic, and population analysis.
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