In the previous post, a method for generating two sequences of correlated random variables was discussed. Generation of multiple sequences of correlated random variables, given a correlation matrix is discussed…

# Tag: cholesky

Any \( n \times n\) symmetric positive definite matrix \( A \) can be factored as $$ A=LL^T $$ where \( L \) is \(n \times n\) lower triangular matrix.…

It is often required to check if a given matrix is positive definite or not. Three methods to check the positive definiteness of a matrix were discussed in a previous…

Forward Substitution: Consider a set of equations in a matrix form \(Ax=b \), where A is a lower triangular matrix with non-zero diagonal elements. The equation is re-written in full…

Matrix inversion is seen ubiquitously in signal processing applications. For example, matrix inversion is an important step in channel estimation and equalization. For instance, in GSM normal burst, 26 bits…

I thought of making a post on Cholesky Decomposition, which is a very essential technique in digital signal processing applications like generating correlated random variables, solving linear equations, channel estimation…

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