Get this from a library! Blind deconvolution. [Simon S Haykin;]. Keywords. Speech Signal Blind Signal Separation Algorithm Blind Deconvolution Nonstationary Signal Haykin S () Blind deconvolution. Prentice Hall. Description. A complete, one-stop reference on the state of the art of unsupervised adaptive filtering. While unsupervised adaptive filtering has its roots in the.
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Pearson offers special pricing when you package your text with other student resources. Series Adaptive and Cognitive Dynamic Systems: B55 Book; Illustrated English Show 0 more libraries In order to set up a list of libraries that you have access to, you must first login or sign up. Through contributions by the foremost experts on the subject, the book provides an up-to-date account of research findings, explains the underlying theory, and discusses potential applications in diverse fields.
Series Prentice Hall information and system sciences series Subjects Signal processing — Mathematics.
Unsupervised Adaptive Filtering, Volume 2, Blind Deconvolution
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Set up My libraries How do I set up “My libraries”? The Single-User Equalization Problem 4. Douglas and Simon Haykin 3. You have successfully signed out and will be required to sign back in should you need to download blinc resources. Lists What are lists? This single location in Queensland: Request permission to reuse content deconvolutoon this site.
Divided into two volumes for ease of presentation, this important work shows how these algorithms, deconvolutiion developed independently, are closely related foundations of unsupervised adaptive filtering. Then set up a personal list of libraries from your profile page by clicking on your user name at the top right of any screen.
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Blind deconvolution / Simon Haykin, editor. – Version details – Trove
More than illustrations as well as case studies, appendices, and references further enhance this excellent resource. View online Borrow Buy Freely available Show 0 more links Tags What are tags? Physical Description ix, p. Description A complete, one-stop reference on the state of the art of unsupervised adaptive filtering While unsupervised adaptive filtering has its roots in the s, more recent advances in signal processing, information theory, imaging, and remote sensing have made this a hot area for research in several diverse fields.
If You’re a Student Additional order info. The MUK Approach 4. If you’re interested in creating a cost-saving package for your students, contact your Pearson rep. Blind Source Separation, this volume discusses: Following coverage begun in Volume I: Read an Excerpt Excerpt 1: Published Englewood Cliffs, B,ind. Found at these bookshops Searching – please wait Added to Your Shopping Cart.
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