A class of damped Morozov principles is introduced to determine the re
gularization parameter for the least squares formulation of nonlinear
illposed inverse problems. Their asymptotic behavior as the error leve
l in the data converges to zero is studied and a numerical example is
given which shows that a damped Morozov principle can be superior to t
he Morozov principle.