Three recursive methods especially suited for identification of systems with rapidly changing parameters are applied to tracking of the viscoelastic properties of the systemic arterial bed. These methods include two least squares (LS) algorithms with constant or variable forgetting factor (RLS and LSVF) and a LS algorithm incorporating both a constant forgetting factor and covariance modification (CFCM). The methods are presented in a unified framework and their sensitivity with respect to the design variables is investigated using noisy data from computer simulations. All analysed methods have shown themselves to be able to satisfactory track rapid changes in peripheral resistance. The LSVF method, which offers slightly better performances than the classical RLS, may be preferred when calculation efficiency is the prime requirement. The CFCM algorithm, although maintaining reasonable simplicity, shows the best tracking ability also on varying of the noise sequence.