ComplexNormal(μ,σ)

• μ : mean, μ = 0 by default
• σ : standard deviation, σ =1 by default

# Examples

# Generates 10 iid standard Complex Gaussian r.v.s
rand(ComplexNormal(), 10) 

# Generates complex normal with mean 1+1im, variance 4
rand(ComplexNormal(1+1im,2)) 

Gaussian(beta,μ,σ)

• beta : 1 (default) for Real Gaussian, 2 for Complex Gaussian
• μ : mean, μ = 0 by default
• σ : standard deviation, σ =1 by default

# Generates 10 iid standard normal r.v.s
rand(Gaussian(), 10) 

# Generates a complex normal with mean 1+1im, variance 4
rand(Gaussian(2,1+1im,2))

±(a,b)

• returns (a-b,a+b)

# Examples

1 ± 0.5  # returns (0.5,1.5)

# Example

# The resolvent of a random Hermitian matrix is approximately diagonal, 
# see Section 3 in https://arxiv.org/pdf/1903.10060.pdf
 normview(resolvent(randHermitian(1000,norm=true))(0.5+0.1im))

randSampling(A::Matrix, B=I::Matrix; k=0::Int)

Generate a random sampling random Matrix S, E(SS')=I. ASS'B is typically used to approximate AB.

Examples

S = randSampling(rand(2,3),rand(3,2),k=2)

3×2 Matrix{Float64}:
 0.0      0.0
 0.0      1.2439
 1.15342  0.0