{"product_id":"9781118211212","title":"Kernel Adaptive Filtering: A Comprehensive Introduction","description":"\u003cb\u003eOnline learning from a signal processing perspective\u003c\/b\u003e \u003cp\u003eThere is increased interest in kernel learning algorithms in neural networks and a growing need for nonlinear adaptive algorithms in advanced signal processing, communications, and controls. \u003ci\u003eKernel Adaptive Filtering\u003c\/i\u003e is the first book to present a comprehensive, unifying introduction to online learning algorithms in reproducing kernel Hilbert spaces. Based on research being conducted in the Computational Neuro-Engineering Laboratory at the University of Florida and in the Cognitive Systems Laboratory at McMaster University, Ontario, Canada, this unique resource elevates the adaptive filtering theory to a new level, presenting a new design methodology of nonlinear adaptive filters.\u003c\/p\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eCovers the kernel least mean squares algorithm, kernel affine projection algorithms, the kernel recursive least squares algorithm, the theory of Gaussian process regression, and the extended kernel recursive least squares algorithm\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003ePresents a powerful model-selection method called maximum marginal likelihood\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eAddresses the principal bottleneck of kernel adaptive filters—their growing structure\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eFeatures twelve computer-oriented experiments to reinforce the concepts, with MATLAB codes downloadable from the authors' Web site\u003c\/p\u003e \u003c\/li\u003e \u003cli\u003e \u003cp\u003eConcludes each chapter with a summary of the state of the art and potential future directions for original research\u003c\/p\u003e \u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eKernel Adaptive Filtering\u003c\/i\u003e is ideal for engineers, computer scientists, and graduate students interested in nonlinear adaptive systems for online applications (applications where the data stream arrives one sample at a time and incremental optimal solutions are desirable). It is also a useful guide for those who look for nonlinear adaptive filtering methodologies to solve practical problems.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47113719152880,"sku":"9781118211212","price":122.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0737\/7593\/9824\/files\/9781118211212_p0.jpg?v=1769888188","url":"https:\/\/shop-qa.barnesandnoble.com\/products\/9781118211212","provider":"Barnes \u0026 Noble (DEV)","version":"1.0","type":"link"}