Recursive identification algorithms based on least square estimation procedure have been presented for both linear and a class of nonlinear systems. The linear system is represented by an impulse response model while the non-linear system is a cascade combination of a. linear part and u zero memory non-linear part. It has been shown that even in the presence of coloured noise, for the model selected, ordinary least square estimation gives unbiased estimates of the system parameters. Results are illustrated through suitable numerical examples.