Segmentation of non-stationary signals with applications
Nonstationary signals are partitioned into near-stationary segments using a modified Appel and Brandt algorithm. The modification requires two spectral distance measures to be used to produce an algorithm which is insensitive to changes in signal energy level which are irrelevant in this application. Performance on real and simulated data is presented. Segmentation has been used to provide an estimator of the evolutive spectrum, an application to a noisy communication signal is presented.<<ETX>>