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Mathematics for Future Computing and Communications 🔍
Liao Heng (editor), Bill McColl (editor) Cambridge University Press (Virtual Publishing), New, 2021
英语 [en] · PDF · 18.0MB · 2021 · 📘 非小说类图书 · 🚀/lgli/lgrs/nexusstc/upload/zlib · Save
描述
For 80 years, mathematics has driven fundamental innovation in computing and communications. This timely book provides a panorama of some recent ideas in mathematics and how they will drive continued innovation in computing, communications and AI in the coming years. It provides a unique insight into how the new techniques that are being developed can be used to provide theoretical foundations for technological progress, just as mathematics was used in earlier times by Turing, von Neumann, Shannon and others. Edited by leading researchers in the field, chapters cover the application of new mathematics in computer architecture, software verification, quantum computing, compressed sensing, networking, Bayesian inference, machine learning, reinforcement learning and many other areas. -- Provided by publisher
备用文件名
nexusstc/Mathematics for Future Computing and Communications/d714dac2664990fa5b52b601a6d66993.pdf
备用文件名
lgli/Mathematics for Future Computing and Communications.pdf
备用文件名
lgrsnf/Mathematics for Future Computing and Communications.pdf
备用文件名
zlib/no-category/Liao Heng (editor), Bill McColl (editor)/Mathematics for Future Computing and Communications_21309787.pdf
备选作者
Heng Liao; Bill McColl
备选作者
Bill McColl; Liao Heng
备用出版商
University of Cambridge ESOL Examinations
备用出版商
RCOG Press
备用版本
United Kingdom and Ireland, United Kingdom
备用版本
Cambridge, United Kingdom, 2022
备用版本
Cambridge, 2021
备用版本
New, PS, 2022
元数据中的注释
{"isbns":["1009070215","1316513580","9781009070218","9781316513583"],"last_page":396,"publisher":"Cambridge University Press"}
备用描述
New mathematical ideas go hand-in-hand with innovation in computing, communications and AI. Such innovations are described here in a book that provides a panorama of ideas and applications in computer architecture, software verification, quantum computing, compressed sensing, Bayesian inference, machine learning, reinforcement learning and more.
开源日期
2022-04-10
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