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As [16, 20, 21], based on the coherent nature of SAR, under the Gaussian scatterer assumption, can be modeled by a multivariate, complex, zero-mean, Gaussian probability density function (pdf): (4).
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In this experiment, we compared the seven methods shown in Fig. 1, namely, Laplace IVA (optimized by IP) [49], GGD-IVA (optimized by IP) [17], MNMF (based on a multivariate complex Gaussian distribution) [32], t-MNMF [40], ILRMA (based on a complex Gaussian distribution with a time-frequency-varying variance) [34], GGD-ILRMA, and t-ILRMA.
The multivariate complex normal distribution of a P-dimensional random vector is denoted by (mathcal {C}mathcal {N}(boldsymbol {mu }, boldsymbol {Sigma })) where μ is the P-dimensional mean vector and Σ the P×P covariance matrix.
denotes expectation, and denotes a multivariate proper complex normal distribution with mean vector and covariance matrix.
First, the multivariate distribution of the asset returns is fitted by a multivariate distribution.
All these techniques are strongly supported by a multivariate approach.
Risk factors were evaluated by a multivariate logistic regression model.
The impact on duration of stay was estimated by a multivariate Poisson regression.
Therefore, the distribution of market returns is fitted by a multivariate distribution.
The CPE method was optimized by a multivariate approach (two-level full factorial and Doehlert designs).
This was further confirmed by a multivariate analysis of variance (MANOVA) test.
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