This paper presents an approach to reduce the computational burden of typical recursive algorithms used for real-time system identification applications. Recursive algorithms contain two updates per iteration cycle; the Covariance Matrix Approximation (CMA) update and the gradient vector update. Usually, the computational effort of updating CMA is much higher than that of updating gradient vector. Therefore, re-using CMA, calculated from the last iteration cycle, for the next iteration can result in computational cost savings. In the paper, this technique is applied for both RLS and AP algorithms, for the purpose of identifying the parameters of a three-rail power converter.