On minimal singular values of random matrices with correlated entries (1309.5711v1)
Abstract: Let $\mathbf X$ be a random matrix whose pairs of entries $X_{jk}$ and $X_{kj}$ are correlated and vectors $ (X_{jk},X_{kj})$, for $1\le j<k\le n$, are mutually independent. Assume that the diagonal entries are independent from off-diagonal entries as well. We assume that $\mathbb{E} X_{jk}=0$, $\mathbb{E} X_{jk}^2=1$, for any $j,k=1,\ldots,n$ and $\mathbb{E} X_{jk}X_{kj}=\rho$ for $1\le j<k\le n$. Let $\mathbf M_n$ be a non-random $n\times n$ matrix with $\|\mathbf M_n\|\le Kn^Q$, for some positive constants $K\>0$ and $Q\ge 0$. Let $s_n(\mathbf X+\mathbf M_n)$ denote the least singular value of the matrix $\mathbf X+\mathbf M_n$. It is shown that there exist positive constants $A$ and $B$ depending on $K,Q,\rho$ only such that $$ \mathbb{P}(s_n(\mathbf X+\mathbf M_n)\le n{-A})\le n{-B}. $$ As an application of this result we prove the elliptic law for this class of matrices with non identically distributed correlated entries.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.