Sentence examples for matrix estimation requires from inspiring English sources

The second, dedicated to mixing matrix estimation, requires fixing two parameters only, regardless of the instrumented SNRs.

These two hypothesis testing problems are different in that mixing matrix estimation requires selecting points where only one single source is present, whereas this constraint is useless for denoising and source recovery.

The second one is dedicated to autosource selection for mixing matrix estimation and requires fixing two parameters only, regardless of the instrumented SNRs.

However, the MMSE channel estimation requires prior knowledge of the channel coefficient covariance matrix RH and noise covariance matrix RH, which means that the MMSE method is more complicated than the LS approach.

Formation of regions and quantile estimation requires discerning information from fuzzy-membership matrix obtained based on the approach.

Since the conventional LMMSE channel estimation requires the channel statistics, that is, the channel autocorrelation matrix in frequency domain and SNR, which are often unavailable in practical systems, the application of the conventional LMMSE channel estimation is limited.

The ψ estimation requires one sine operation.

Since each estimation requires the other one, the algorithm is iterative, as proposed in [34] for a theoretical case in which the channel covariance matrix is supposed to be known at the receiver.

Therefore, estimation requires assumptions to be made.

However, this estimation requires confirmation by further investigations.

In [16], the minimization problem is solved based on the covariance matrix estimation approach which requires a large number of snapshots.