Title :
Generalized canonical variate analysis of nonlinear systems
Author :
Larimore, Wallace E.
Author_Institution :
Comput. Eng. Inc., Woburn, MA, USA
Abstract :
The canonical variate analysis (CVA) is extended to general nonlinear systems. Nonlinear canonical variables are shown to determine the optimum nonlinear transformation of the past maximizing the mutual information between the true and an approximating normal distribution. A sequential procedure for selection of the canonical variables is described. Nonlinear CVA is applied to nonlinear controlled Markov processes to obtain approximating nonlinear filters. A recursive innovations representation is given for the nonlinear filter that also yields an innovations representation for the Markov process model
Keywords :
Markov processes; filtering and prediction theory; nonlinear systems; approximating nonlinear filters; canonical variate analysis; nonlinear controlled Markov processes; nonlinear systems; optimum nonlinear transformation; recursive innovations representation; Business; Density measurement; Gaussian distribution; Hilbert space; Markov processes; Mutual information; Nonlinear filters; Nonlinear systems; Random variables; Technological innovation;
Conference_Titel :
Decision and Control, 1988., Proceedings of the 27th IEEE Conference on
Conference_Location :
Austin, TX
DOI :
10.1109/CDC.1988.194622
