**Complex Random Vectors**

The variance of a complex scalar-valued random variable with expected value μ is conventionally defined using complex conjugation:

where the complex conjugate of a complex number is denoted ; thus the variance of a complex number is a real number.

If is a column-vector of complex-valued random variables, then the conjugate transpose is formed by *both* transposing and conjugating. In the following expression, the product of a vector with its conjugate transpose results in a square matrix, as its expectation:

where denotes the conjugate transpose, which is applicable to the scalar case since the transpose of a scalar is still a scalar. The matrix so obtained will be Hermitian positive-semidefinite, with real numbers in the main diagonal and complex numbers off-diagonal.

Read more about this topic: Covariance Matrix

### Famous quotes containing the words complex and/or random:

“We must open our eyes and see that modern civilization has become so *complex* and the lives of civilized men so interwoven with the lives of other men in other countries as to make it impossible to be in this world and out of it.”

—Franklin D. Roosevelt (1882–1945)

“Novels as dull as dishwater, with the grease of *random* sentiments floating on top.”

—Italo Calvino (1923–1985)