Sentence examples for multidimensional parameter estimation from inspiring English sources

In this section, we present the multidimensional parameter estimation algorithm in polarimetric MIMO radar using PARAFAC quadrilinear decomposition.

Thus, PARAFAC quadrilinear decomposition [22, 23] with quadrilinear alternating least square (QALS) is applied to multidimensional parameter estimation in polarimetric bistatic MIMO radar.

From Figure 2, we observe that the performance of multidimensional parameter estimation has been improved gradually with the increase of SNR.

In this article, we investigate multidimensional target parameter estimation in a polarimetric bistatic MIMO radar system using PARAFAC quadrilinear decomposition.

In this article, we investigate the problem of applying the parallel factor quadrilinear decomposition technique to multidimensional target parameter estimation in a polarimetric bistatic multiple-input multiple-output (MIMO) radar system with a uniform rectangular array at the transmitter and a cross-dipole-based uniform rectangular array at the receiver.

Note that the obtained real-valued tensor-based subspace estimate can be employed in the unitary tensor ESPRIT algorithm [10] for parameter estimation in multidimensional harmonic retrieval problems.

Parameter estimation of multidimensional data in the presence of colored noise or interference with a Kronecker product covariance structure, which appears in electroencephalogram/magnetoencephalogram and multiple-input multiple-output applications, is addressed.

In addition, other computational factors such as finding the global optimal solution over highly multidimensional parameter space and integrating stiff ODEs, often make the parameter estimation numerically intractable, even for models with 10 20 parameters [ 5].

Simulation-based parameter estimation offers a powerful means of estimating parameters in complex stochastic models.

We investigate possibilities of choosing an activation policy of discrete scanning sensors in such a way as to maximize the accuracy of parameter estimation of a distributed system defined in a given multidimensional domain.

In time-varying multidimensional harmonic retrieval problems, we use the subspace estimates tracked via the TeTraKron-based subspace tracking schemes in ESPRIT-type parameter estimation algorithms [10] and evaluate their resulting performances.