zero-mean, circular-symmetric complex Gaussian-distributed elements of variance.
zero-mean, circular-symmetric complex Gaussian-distributed elements of variance, (vi) is the channel matrix from the source to destination with i.i.d.i.d
zero-mean, circular-symmetric complex Gaussian-distributed elements of variance, is the channel matrix from the source to destination with i.i.d.i.d
zero-mean, circular-symmetric complex Gaussian-distributed elements of variance (i.e., the real and imaginary parts of each elements are independent zero-mean Gaussian random variables with the same variance), is the noise vector with i.i.d.i.d
zero-mean, circular-symmetric complex Gaussian-distributed elements of variance (i.e., the real and imaginary parts of each elements are independent zero-mean Gaussian random variables with the same variance), (v) is the noise vector with i.i.d.i.d
V i is constructed as V i = ϕ B i 1 / 2 R α B i 1 / 2, where B i = diag b ″ θ i t is a diagonal matrix with main diagonal elements of variance function, b ″ θ i t, and R is a correlation matrix.
Yet, it is an element of the variance that can be measured very precisely and will play an important role in the design of future studies.
Relationships between genotyped animals (1,989 diagonal and 3,954,132 off-diagonal elements) Estimates of variance components obtained with the full data set are in Table 2, and estimates from the subset are in Table 3.
The ijth element of the variance-covariance matrix V (the covariance between xi and xj when i≠j and Vii is the variance of xi) is calculated as V i j = max Q i j L, where, Q i j L = 1 2 n 2 ∑ a ∑ b x i a - x i b ′ L x j a - x j b, Where, L is an orthogonal matrix (orthogonal transformation) [ 30], in our case L = 1.
Rayleigh fading elements of unit variance: h i k ∑ ℂ N ( 0, I N t ).
