By Weifeng Liu, Jose C. Principe, Simon Haykin

ISBN-10: 0470447532

ISBN-13: 9780470447536

### Kurzbeschreibung

Online studying from a sign processing perspective

There is elevated curiosity in kernel studying algorithms in neural networks and a turning out to be want for nonlinear adaptive algorithms in complex sign processing, communications, and controls. Kernel Adaptive Filtering is the 1st e-book to offer a finished, unifying creation to on-line studying algorithms in reproducing kernel Hilbert areas. according to examine being carried out within the Computational Neuro-Engineering Laboratory on the college of Florida and within the Cognitive structures Laboratory at McMaster collage, Ontario, Canada, this specified source elevates the adaptive filtering thought to a brand new point, proposing a brand new layout method of nonlinear adaptive filters.

* Covers the kernel least suggest squares set of rules, kernel affine projection algorithms, the kernel recursive least squares set of rules, the speculation of Gaussian approach regression, and the prolonged kernel recursive least squares algorithm*

offers a strong model-selection procedure referred to as greatest marginal likelihood

* Addresses the primary bottleneck of kernel adaptive filters--their turning out to be structure*

positive factors twelve computer-oriented experiments to enhance the innovations, with MATLAB codes downloadable from the authors' internet site

* Concludes every one bankruptcy with a precis of the state-of-the-art and capability destiny instructions for unique research

Kernel Adaptive Filtering is perfect for engineers, laptop scientists, and graduate scholars drawn to nonlinear adaptive platforms for on-line functions (applications the place the information circulation arrives one pattern at a time and incremental optimum ideas are desirable). it's also an invaluable consultant if you search for nonlinear adaptive filtering methodologies to resolve sensible difficulties.

### Buchrückseite

Online studying from a sign processing perspective

There is elevated curiosity in kernel studying algorithms in neural networks and a becoming want for nonlinear adaptive algorithms in complicated sign processing, communications, and controls. Kernel Adaptive Filtering is the 1st ebook to offer a entire, unifying advent to on-line studying algorithms in reproducing kernel Hilbert areas. in response to examine being performed within the Computational Neuro-Engineering Laboratory on the collage of Florida and within the Cognitive structures Laboratory at McMaster collage, Ontario, Canada, this certain source elevates the adaptive filtering concept to a brand new point, providing a brand new layout method of nonlinear adaptive filters.

* Covers the kernel least suggest squares set of rules, kernel affine projection algorithms, the kernel recursive least squares set of rules, the idea of Gaussian procedure regression, and the prolonged kernel recursive least squares algorithm*

provides a robust model-selection approach referred to as greatest marginal likelihood

* Addresses the relevant bottleneck of kernel adaptive filters--their starting to be structure*

positive aspects twelve computer-oriented experiments to augment the techniques, with MATLAB codes downloadable from the authors' net site

* Concludes every one bankruptcy with a precis of the cutting-edge and power destiny instructions for unique research

Kernel Adaptive Filtering is perfect for engineers, computing device scientists, and graduate scholars attracted to nonlinear adaptive platforms for on-line purposes (applications the place the information circulation arrives one pattern at a time and incremental optimum options are desirable). it's also an invaluable advisor if you search for nonlinear adaptive filtering methodologies to resolve functional difficulties.