Kernel adaptive filtering a comprehensive introduction

Multiple-input, multiple-output channel models theory and practice

Complex valued nonlinear adaptive filters noncircularity, widely linear and neural models

Bayesian signal processing classical, modern, and particle filtering methods

Knowledge based radar detection, tracking, and classification

Correlative learning a basis for brain and adaptive systems

Adaptive approximation based control unifying neural, fuzzy and traditional adaptive approximation approaches

Least-mean-square adaptive filters

Stable adaptive control and estimation for nonlinear systems neural and fuzzy approximator techniques

Recurrent neural networks for prediction learning algorithms, architectures, and stability

Kalman filtering and neural networks

Independent component analysis