Derivative domain fitting: A new method for resolving a mixture of normal distributions in the presence of a contaminating background

Derivative domain least squares analysis is a new method for resolving multiple peaks superimposed on a slowly varying continuum into separate normal (Gaussian) distributions without developing a functional approximation for the continuum. The method is based on fitting the first derivative of the data with the first derivative of the sum of a series of normal distributions. A functional approximation for the continuum is not necessary as long as the first derivative of the continuum is approximately zero (i.e., the continuum varies slowly compared to the normal distributions). © 1993 Wiley‐Liss, Inc.