Approximate and Noise Realization of Discrete-Time Dynamical Systems deals with approximation and noise cancellation of dynamical systems, which include linear and nonlinear input/output relations. It will be of special interest to researchers, engineers and graduate students who specializing in filtering and system theory. Using state-space-based analysis, model reduction has become a majoro theme of technological development, emphasizing efficiency in fields including control, economics and numerical analysis. Noise reduction problems in the have also become a significant are of study, though for the most part in linear systems.

A new method, which reduces noise or models information is proposed. Using this method allows the model description to be treated as noise reduction or model reduction. Reduction is made from noisy or noiseless data. As proof of this method’s efficacy, this book provides results and extensions that can also be applied to nonlinear dynamical systems. To demonstrate the effectiveness of the method, the authors provide many examples of noise and model information reduction