| A systematic optimization of the Cohen class time-frequency transformation for detecting the parameters change is developed. The local moments approach to change detection is proposed and a general formula for the local moments is derived. The optimal kernel functions of the time-frequency transformation are determined based on the combined criteria of maximum sensitivity with respect to parameters change and minimum distortion of physical interpretation of the local moments. The sensitivity of the local moment with respect to a certain kind of inputs is analyzed and a most "convenient" and a "worst" input are identified. The results are presented in the form of the case studies for detecting parameters change in simple linear systems. |
