Analysis and representation of composite signals by cepstral inverse filtering

This paper describes a new technique for constructing representations of signals belonging to a class that includes arterial blood pressure waves and voiced speech. Called cepstral inverse filtering, it optimizes the pole and zero locations of a discrete-time system that models the signal production process. These locations are chosen so that the cepstrum of the model impulse response is a least-squares estimate of that of the signal under analysis. The iterative procedure employed in solving this non-linear estimation problem is made computationally efficient through the use of simple digital filtering techniques.