Identification, Adaptation, Learning: The Science of Learning Models from Data (Hardcover, 1996)

Geometric Methods for State Space Identification.- Parameter Estimation of Multivariable Systems Using Balanced Realizations.- Balanced Canonical Forms.- From Data to State Model.- Identification of Linear Systems from Noisy Data.- Identification in H?: Theory and Applications.- System Identification with Information Theoretic Criteria.- Least Squares Based Self-Tuning Control Systems.- On Neural Network Model Structures in System Identification.- An Overview of Computational Learning Theory and Its Applications to Neural Network Training.- Just-in-Time Learning and Estimation.- Wavelets in Identification.- Fuzzy Logic Modelling and Control.- Searching for the Best: Stochastic Approximation, Simulated Annealing and Related Procedures.- List of Contributors.