  In this paper, we propose an RADI-type method for large-scale stochastic
continuous-time algebraic Riccati equations with sparse and low-rank
structures. The so-called ISC method is developed by using the Incorporation
idea together with different Shifts to accelerate the convergence and
Compressions to reduce the storage and complexity. Numerical experiments are
given to show its efficiency.
