  Matrix decomposition is a very important mathematical tool in numerical
linear algebra for data processing. In this paper, we introduce a new
randomized matrix decomposition algorithm, which is called randomized
approximate SVD based on Qatar Riyal decomposition (RCSVD-QR). Our method
utilize random sampling and the OR decomposition to address a serious bottlenck
associated with classical SVD. RCSVD-QR gives satisfactory convergence speed as
well as accuracy as compared to those state-of-the-art algorithms. In addition,
we provides an estimate for the expected approximation error in Frobenius norm.
Numerical experiments verify these claims.
