Application of canonical coordinate methods to the characterization of a family of error minimizing signal compression techniques

Mean-square-error minimizing signal compression techniques, such as Autoregressive Analysis or Linear Predictive Coding and Principal Component or Karhunen-Loève Analysis, can be systematically characterized in terms of canonical coordinate or generalized eigenvector procedures. This approach provides considerable insight into the interrelationships between a variety of seemingly different signal compression methods. The approach also provides a convenient mechanism for introducing the types of non-Euclidean error measures that are needed to adjust the signal performance optimization criteria to take into account different types of a priori statistical and dynamical information relating to both the desired signal and to various interference processes.