@article{751675,
      recid = {751675},
      author = {Ozeki, Kazuhiko,},
      title = {Theory of affine projection algorithms for adaptive  filtering [electronic resource] /},
      pages = {1 online resource.},
      abstract = {This book focuses on theoretical aspects of the affine  projection algorithm (APA) for adaptive filtering. The APA  is a natural generalization of the classical, normalized  least-mean-squares (NLMS) algorithm. The book first  explains how the APA evolved from the NLMS algorithm, where  an affine projection view is emphasized. By looking at  those adaptation algorithms from such a geometrical point  of view, we can find many of the important properties of  the APA, e.g., the improvement of the convergence rate over  the NLMS algorithm especially for correlated input signals.  After the birth of the APA in the mid-1980s, similar  algorithms were put forward by other researchers  independently from different perspectives. This book shows  that they are variants of the APA, forming a family of  APAs. Then it surveys research on the convergence behavior  of the APA, where statistical analyses play important  roles. It also reviews developments of techniques to reduce  the computational complexity of the APA, which are  important for real-time processing. It covers a recent  study on the kernel APA, which extends the APA so that it  is applicable to identification of not only linear systems  but also nonlinear systems. The last chapter gives an  overview of current topics on variable parameter APAs. The  book is self-contained, and is suitable for graduate  students and researchers who are interested in advanced  theory of adaptive filtering.},
      url = {http://library.usi.edu/record/751675},
      doi = {https://doi.org/10.1007/978-4-431-55738-8},
}