矩阵分解已经成为统计学的核心技术(Banerjee和Roy, 2014;、优化(Gill et al.， 2021)、机器学习(Goodfellow et al.， 2016);而深度学习在很大程度上是由于反向传播算法在拟合神经网络和低秩神经网络在高效深度学习中的发展。本调查的唯一目的是对数值线性代数和矩阵分析中的概念和数学工具进行一个完整的介绍，以便在后续章节中无缝地介绍矩阵分解技术及其应用。然而，我们清楚地认识到，我们无法涵盖所有关于矩阵分解的有用和有趣的结果，并且给出了这种讨论的范围的缺乏，例如，欧氏空间、厄米特空间和希尔伯特空间的分离分析。我们建议读者参考线性代数领域的文献，以获得相关领域的更详细介绍。一些优秀的例子包括(Householder, 2006; Trefethen and Bau III, 1997; Strang, 2009; Stewart, 2000; Gentle, 2007; Higham, 2002; Quarteroni et al., 2010; Golub and Van Loan, 2013; Beck, 2017; Gallier and Quaintance, 2017; Boyd and Vandenberghe, 2018; Strang, 2019; van de Geijn and Myers, 2020; Strang, 2021)

国外编码纠错的经典教材，介绍了分组码，卷积码等等，作者是SHU LIN/DANIEL J.COSTELLO,JR. 全英文,总共两部分，这里先上传一部分，另外一部分随后跟上 part1

时间序列分析 经典教材 The fourth edition of this popular graduate textbook, like its predecessors, presents a balanced and comprehensive treatment of both time and frequency domain methods with accompanying theory. Numerous examples using nontrivial data illustrate solutions to problems such as discovering natural and anthropogenic climate change, evaluating pain perception experiments using functional magnetic resonance imaging, and monitoring a nuclear test ban treaty. The book is designed as a textbook for graduate level students in the physical, biological, and social sciences and as a graduate level text in statistics. Some parts may also serve as an undergraduate introductory course. Theory and methodology are separated to allow presentations on different levels. In addition to coverage of classical methods of time series regression, ARIMA models, spectral analysis and state-space models, the text includes modern developments including categorical time series analysis, multivariate spectral methods, long memory series, nonlinear models, resampling techniques, GARCH models, ARMAX models, stochastic volatility, wavelets, and Markov chain Monte Carlo integration methods. This edition includes R code for each numerical example in addition to Appendix R, which provides a reference for the data sets and R scripts used in the text in addition to a tutorial on basic R commands and R time series. An additional file is available on the book’s website for download, making all the data sets and scripts easy to load into R.

英文版

NET-Microservices-Architecture-for-Containerized-NET-Applications中文版 第二版

This book can be used in the following ways: 1. For a DSP course with a laboratory component, using parts of Chapters 1–9. If needed, the book can be supplemented with some additional theoretical materials, since its emphasis is on the practical aspects of DSP. It is possible to cover Chapter 7 on adaptive filtering following Chapter 4 on finite impulse response (FIR) filtering (since there is only one example in Chapter 7 that uses materials from Chapter 5). It is my conviction that adaptive filtering should be incorporated into an undergraduate course in DSP. 2. For a laboratory course using many of the examples and experiments from Chapters 1–7 and Chapter 9. The beginning of the semester can be devoted to short programming examples and experiments and the remainder of the semester for a final project. The wide range of sample projects (for both undergraduate and graduate students) discussed in Chapter 10 can be very valuable. 3. For a senior undergraduate or first-year graduate design project course using selected materials from Chapters 1–10. 4. For the practicing engineer as a tutorial and reference, and for workshops and seminars, using selected materials throughout the book.

Modern Mathematics andApplications in Computer Graphics and Vision (2014) Hongyu Guo

这是关于小波变换的电子书，高清，最新版本，经典著作，英文版

qt5_applications-5.15.2.2.1-py3-none-win_amd64.whl

Building Mapping Applications with QGIS 英文无水印原版pdf pdf所有页面使用FoxitReader、PDF-XChangeViewer、SumatraPDF和Firefox测试都可以打开 本资源转载自网络，如有侵权，请联系上传者或csdn删除 查看此书详细信息请在美国亚马逊官网搜索此书