Persistance of excitation on least squares

In least squares parameter estimation schemes "persistency of excitation" conditions on the plant states are required for consistent estimation. Here, these "persistency of excitation" conditions are translated into "sufficiently rich" conditions on the plant noise and inputs. With sufficiently rich input signals, convergence rates of prediction errors improve, as do robustness properties.