In the past decade, primal-dual algorithms have emerged as the most important and useful algorithms from the interior-point class. This book presents the major primal-dual algorithms for linear programming in straightforward terms. A thorough description of the theoretical properties of these methods is given, as are a discussion of practical and computational aspects and a summary of current software. This is an excellent, timely, and well-written work. The major primal-dual algorithms covered in this book are path-following algorithms (short- and long-step, predictor-corrector), potential-reduction algorithms, and infeasible-interior-point algorithms. A unified treatment of superlinear convergence, finite termination, and detection of infeasible problems is presented. Issue relevant to practical implementation are also discussed, including sparse linear algebra and a complete specification of Mehrota's predictor-correction algorithm. Also treated are extensions of primal-dual algorithms to more general problems such as monotone complementarity, semidefinite programming, and general convex programming problems. Some background in linear programming and its associated duality theory, linear algebra, and numerical analysis is helpful, although an extensive appendix ensures that the book is largely self-contained. The book is useful for graduate students and researchers in the sciences and engineering who are interested in using large-scale optimization techniques in their research, including those interested in original research in interior-point methods. Engineers may also find applications to problems of process control, predictive control, or design optimization. The book may also be used as a text for a special topics course in optimization or a unit of a general course in optimization or linear programming. Researchers and students in the field of interior-point methods will find the book invaluable as a reference to the key results, the basic analysis in the

电子结构领域的权威著作 Electronic Structure author: Richard Martin 提供寻找新的半导体材料所必需的知识，计算领域的未来之所在。

有限差分矩阵代码Cahn-Hilliard方程的数值方法 该存储库基于Matthew Geleta提交的论文“ Cahn-Hilliard方程的数值方法”，该论文是牛津大学数学硕士学位的一部分。 运行脚本“ Example_Script.m”以演示有限差分求解器，并进行漂亮的模拟。 运行脚本“ FEM_Cahn_Hilliard_Irregular.m”以查看不规则域上稳态Cahn-Hilliard方程的有限元解。 运行脚本“ FEM_Cahn_Hilliard_Rectangular.m”以查看矩形域上稳态Cahn-Hilliard方程的有限元解。 该存储库包含用于以下方面的MATLAB代码：-具有Neumann边界条件的二维Cahn-Hilliard方程的五个有限差分方案。 -稳态Cahn-Hilliard方程的有限元格式。 -使用二维辛普森规则计算面积积分的函数。 -用于生成动画的功能，这些动画显示了Cahn-Hilliard系统的演变。 -示例脚本（称为“ Example_Script”），用于演示有限差分代码的工作方式。 -在某些函数内部内部调用的某些后台依赖文件。

Computational Methods for Fluid Dynamics JH Ferziger M.Peric 3rd

是文字版的。有关 distributed parameter system identification

this Bayesian signal processing text will provide a much needed “down-to-earth” exposition of modern MC techniques. It is coupled with well-known signal processing model sets along with examples and problems that can be used to solve many real-world problems by practicing engineers and scientists along with entry level graduate students as well as advanced undergraduates and postdoctorates requiring a solid introduction to the “next generation” of model-based signal processing techniques.

Chapter 4 Molecular Cloning Methods (2020)

Open Source Intelligence Methods and Tools focuses on building a deep understanding of how to exploit open source intelligence (OSINT) techniques, methods, and tools to acquire information from publicly available online sources to support intelligence analysis. The harvested data can be used in different scenarios such as financial, crime, and terrorism investigations as well as in more regular tasks such as analyzing business competitors, running background checks, and acquiring intelligence about individuals and other entities. This book will also improve your skills in acquiring information online from the surface web, the deep web, and the darknet. Many estimates show that 90 percent of useful information acquired by intelligence services comes from public sources (in other words, OSINT sources). Social media sites open up numerous opportunities for investigations because of the vast amount of useful information located in one place. For example, you can get a great deal of personal information about any person worldwide by just checking their Facebook page. This book will show you how to conduct advanced social media investigations to access content believed to be private, use advanced search engines queries to return accurate results, search historical deleted versions of websites, track individuals online using public record databases and people-searching tools, locate information buried in the deep web, access and navigate the dark web, collect intelligence from the dark web, view multiple historic satellite images and street views of any location, search geolocation information within popular social media sites, and more. In short, you will learn how to use a plethora of techniques, tools, and free online services to gather intelligence about any target online. OSINT-gathering activities should be conducted secretly to avoid revealing the searcher’s identity. Therefore, this book will teach you how to conceal your digital identity and become anonymous on

Deep Learning Methods and Applications 即邓力、俞栋合英文版PDF，仅用作学习参考，不得用于商业用途

这是关于非线性时间序列非参数与参数模型的电子书，高清，最新版本，经典著作，英文版