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We propose a new method for speech source separation that is based on directionally-disjoint estimation of the transfer functions between microphones and sources at different frequencies and at multiple times.
However, hundreds or thousands of assays would be needed for a real estimation of the transfer efficiency.
The estimation of the transfer rate τ is therefore a coarse estimation that should be re-evaluated in future works including spatial dynamics.
This might be explained by the fact that the estimation of the transfer of organic compounds to ground and surface water is often addressed by mass balance models, which are mechanistic (Mackay et al., 2003).
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It is shown that the asymptotic estimation variance of the transfer function estimate is determined entirely by the non-causal part of Φ eiω) and its first few derivatives evaluated at the poles of the system.
It was found that the Sherwood number (Sh), which is a dimensionless expression of the mass transfer coefficient, has excellent correlation with the Reynolds number (Re); thus, the estimation of the mass transfer performance for a given channel and given operational conditions can be determined using the correlation between Sh and Re.
Estimation of the mass transfer coefficients is performed using macroscopic mass balances.
As we know, in the proposed CFO and SPO estimation algorithms, estimation of the channel transfer function is needed.
Two different techniques are employed in the estimation of the mass transfer parameters and the interaction rate constant.
A major issue for the application of maximum-ratio-combining for multimicrophone setups is the estimation of the acoustic transfer functions.
The choices made for the selection of semi-empirical correlations available in literature for the estimation of the heat transfer coefficients in these conditions are described and justified.
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