02735nam a22003737a 450000100090000000300040000900500170001300800410003001000170007102000250008802000240011303500240013704000220016104200140018305000270019708200170022410000310024124501020027226000560037426000600043030000680049049000270055850400570058552012580064265000360190065000280193665000420196465000340200683000290204085601390206994200160220899900190222495201180224320923822APU20221101111918.0210804s2018 nyua fob 000 0deng d a 2018418584 a9781947487062 (epub) a9781947487055 (pdf) a(OCoLC)on1028642376 aYDXbengcAPUdSF alccopycat00aQC20.7.F67bH37 2018eb04a515/.7232231 aHassanieh, Haitham,94743514aThe sparse Fourier transform :btheory and practice h[electronic resource] /cHaitham Hassanieh. a[New York] : bAssociation for Computing Machinery a[San Rafael, California] : bMorgan & Claypool,cc2018. a1 online resources (xvii, 260 pages) :billustrations, charts ;1 aACM book series ;v#19 aIncludes bibliographical references (pages 249-260). a"The Fourier transform is one of the most fundamental tools for computing the frequency representation of signals. It plays a central role in signal processing, communications, audio and video compression, medical imaging, genomics, astronomy, as well as many other areas. Because of its widespread use, fast algorithms for computing the Fourier transform can benefit a large number of applications. The fastest algorithm for computing the Fourier transform is the Fast Fourier Transform (FFT), which runs in near-linear time making it an indispensable tool for many applications. However, today, the runtime of the FFT algorithm is no longer fast enough especially for big data problems where each dataset can be few terabytes. Hence, faster algorithms that run in sublinear time, i.e., do not even sample all the data points, have become necessary. This book addresses the above problem by developing the Sparse Fourier Transofrm algorithms and building practical systems that use these algorithms to solve key problems in six different applications: wireless networks; mobile systems; computer graphics; medical imaging; biochemistry; and digital circuits. This is a revised version of the thesis that won the 2016 ACM Doctoral Dissertation Award" -- 0aFourier transformations.947436 0aSparse matrices.947437 7aFourier transformations.2fast947436 7aSparse matrices.2fast947437 0aACM books ;v#19.947379 uhttps://dl-acm-org.ezproxy.apiit.edu.my/doi/book/10.1145/3166186zAvailable in ACM Digital Library. Requires Log In to view full text. 2lcccE-Book c383495d383495 00102lcc40708E-BookaAPUbAPUcOND d2022-11-01eOTHERSl0oQC20.7.F67 H37 2018ebr2022-11-01w2022-11-01yGC