Adaptive Signal Processing, Next-Generation Solutions，2010

Adaptive filters play a very important role in most of today’s signal processing and control applications as most real-world signals require processing under conditions that are difficult to specify a priori. They have been successfully applied in such diverse fields as communications, control, radar, and biomedical engineering, among others. The field of classical adaptive filtering is now well established and a number of key references—a widely used one being the book Adaptive Filter Theory by Simon Haykin—provide a comprehensive treatment of the theory and applications of adaptive filtering. A number of recent developments in the field, however, have demonstrated how significant performance gains could be achieved beyond those obtained using the standard adaptive filtering approaches. To this end, those recent developments have propelled us to think in terms of a new generation of adaptive signal processing algorithms. As data now come in a multitude of forms originating from different applications and environments, we now have to account for the characteristics of real life data: † Non-Gaussianity; † Noncircularity; † Nonstationarity; and † Nonlinearity. Such data would typically exhibit a rich underlying structure and demand the development of new tools, hence, the writing of this new book.