This chapter deals with the description, the parametric estimation, the state estimation, and the parametric and state estimation conjointly of nonlinear systems. The focus is on the class of nonlinear systems, which are described by Wiener state-space discrete-time mathematical models. Thus, the authors develop a new recursive parametric estimation algorithm, which is based on least squares te...

-We develop a method of performing pattern recognition (discrimination and classification) using a recursive technique derived from mixture models, kernel estimation and stochastic approximation. Unsupervised learning Density estimation Kernel estimator Mixture model Stochastic approximation Recursive estimation

The seminal work on set membership state estimation [1] F. C. Schweppe. Recursive state estimation: unknown but bounded errors and system inputs. [2] D. P. Bertsekas and I. B. Rhodes. Recursive state estimation for a set-membership description of uncertainty.