Selection of a time-varying Volterra model using multiple hypothesis testing

We consider the system identification problem using a time-varying quadratic Volterra model. To enable identification a set of known basis sequences are used in the model to approximate the time-variation of the true system. To reduce the number of parameters in the model we wish to determine which individual sequences are significant in this approximation. Multiple hypothesis testing procedures are employed to select significant sequences. The tests include the Bonferroni test, Holm´s (1979) sequentially rejective Bonferroni test, and Hommel´s (1988) extension to Simes´ (1986) procedure [5].