The recording of somatosensory evoked potentials (SEP) provides an elegant and reliable estimation of the severity of SAE [ 11].
Emile and Comon[44] proposed an elegant blind time delay estimation algorithm for a simplified convolutive mixture: x 1 ( t ) = s 1 ( t ) + s 2 ( t ) + ⋯ + s N sig ( t ) + b 1 ( t ) x 2 ( t ) = α 1 s 1 ( t − τ 1 ) + α 2 s 2 ( t − τ 2 ) + ⋯ + α N sig s N sig ( t − τ N sig ) + b 2 ( t ).
Similar to the single-filter LN model, this multi-filter model draws part of its appeal from the existence of simple and elegant techniques for parameter estimation from experiments.
The solution is an elegant application of statistical sampling and estimation theories to such an important real-world problem.
In an elegant recent study, using a computerised estimation of Psm before and after fluid infusion, Cecconi et al. reported similar results, with a significant increase in the Psm-CVP gradient in fluid-responders and no change in this gradient in fluid-nonresponders [ 18].
An elegant application of the EM algorithm in estimation of missing data is given by Longford et al [ 24].
Furthermore, as compared with the use of the GF in (3), using the GGF in (4) offers a simpler way for the estimation of the mixing matrix due to the exploitation of an elegant algebraic structure.
Statistical inference provides an elegant framework to deal with this problem, but these methods are usually intended for single instrument f0 estimation (typically piano), as exact inference often becomes computationally intractable for complex and very different sources.
