机器人学中的圣经，做运动规划的手头书籍，可惜国内没有引进，这是.chm格式的电子版，方便大家阅读和查找章节。作者之一是Lydia E. Kavraki，相信做运动规划的同学都知道她。从位姿空间到一些传统的规划方法，如势场法到概率完备的规划方法如PRM，RRT等，全都有详细讲解。

作者: Sanjoy Dasgupta, Christos Papadimitriou, Umesh Vazirani 译者: 王沛, 唐扬斌, 刘齐军 译者序 算法是当代信息技术的重要基石，同时也是计算科学研究的一项永恒主题。 早在许多世纪以前，算法研究就已经从数学，特别是算术研究中崭露头角。 个人收集电子书，仅用学习使用，不可用于商业用途，如有版权问题，请联系删除

latex Algorithms伪代码规范, 详细介绍了伪代码需要调用的包，以及修改algorithms的默认设置。阐述了原理

Bioinformatics Algorithms: An Active Learning Approach 2nd Edition, Vol. I by Phillip Compeau & Pavel Pevzner

Two Dimensional Phase Unwrapping Theory Algorithms, and Software 书中程序代码

Convex Analysis and Minimization Algorithms II Advanced Theory and Bundle Methods Authors: Hiriart-Urruty, Jean-Baptiste, Lemarechal, Claude From the reviews: "The account is quite detailed and is written in a manner that will appeal to analysts and numerical practitioners alike...they contain everything from rigorous proofs to tables of numerical calculations.... one of the strong features of these books...that they are designed not for the expert, but for those who whish to learn the subject matter starting from little or no background...there are numerous examples, and counter-examples, to back up the theory...To my knowledge, no other authors have given such a clear geometric account of convex analysis." "This innovative text is well written, copiously illustrated, and accessible to a wide audience"

Graph Algorithms by Mark Needham and Amy E. Hodler Copyright © 2019 Amy Hodler and Mark Needham. All rights reserved. What’s in This Book This book is a practical guide to getting started with graph algorithms for developers and data scientists who have experience using Apache Spark™ or Neo4j. Although our algorithm examples utilize the Spark and Neo4j platforms, this book will also be helpful for understanding more general graph concepts, regardless of your choice of graph technologies. The first two chapters provide an introduction to graph analytics, algorithms, and theory. The third chapter briefly covers the platforms used in this book before we dive into three chapters focusing on classic graph algorithms: pathfinding, centrality, and community detection. We wrap up the book with two chapters showing how graph algorithms are used within workflows: one for general analysis and one for machine learning. At the beginning of each category of algorithms, there is a reference table to help you quickly jump to the relevant algorithm. For each algorithm, you’ll find: • An explanation of what the algorithm does • Use cases for the algorithm and references to where you can learn more • Example code providing concrete ways to use the algorithm in Spark, Neo4j, or both 图方法方面最新的参考书，本文理论实践兼备（看标题就知道了），内容高清无码书签完整诚不我欺，强烈推荐给需要的朋友！

Before there were computers, there were algorithms. But now that there are computers, there are even more algorithms, and algorithms lie at the heart of computing. This book provides a comprehensive introduction to the modern study of computer algorithms. It presents many algorithms and covers them in considerable depth, yet makes their design and analysis accessible to all levels of readers. We have tried to keep explanations elementary without sacrificing depth of coverage or mathematical rigor. Each chapter presents an algorithm, a design technique, an application area, or a related topic. Algorithms are described in English and in a pseudocode designed to be readable by anyone who has done a little programming. The book contains 244 figures—many with multiple parts—illustrating how the algorithms work. Since we emphasize efficiency as a design criterion, we include careful analyses of the running times of all our algorithms. The text is intended primarily for use in undergraduate or graduate courses in algorithms or data structures. Because it discusses engineering issues in algorithm design, as well as mathematical aspects, it is equally well suited for self-study by technical professionals. In this, the third edition, we have once again updated the entire book. The changes cover a broad spectrum, including new chapters, revised pseudocode, and a more active writing style.

Introduction to Algorithms (3rd Edition).pdf 算法导论 第三版 英文原版 非扫描版

What this book covers Chapter 1, Hello Rust!, gives a short recap of the Rust programming language and what changed in the 2018 edition. Chapter 2, Cargo and Crates, discusses Rust's cargo build tool. We will explore the configuration as well as the build process and modularization options. Chapter 3, Storing Efficiently, looks at how in Rust, knowing where values are stored is not only important for performance, but also important for understanding error messages and the language in general. In this chapter, we think about stack and heap memory. Chapter 4, Lists, Lists, and More Lists, covers the first data structures: lists. Using several examples, this chapter goes into variations of sequential data structures and their implementations. Chapter 5, Robust Trees, continues our journey through popular data structures: trees are next on the list. In several detailed examples, we explore the inner workings of these efficient designs and how they improve application performance considerably. Chapter 6, Exploring Maps and Sets, explores the most popular key-value stores: maps. In this chapter, techniques surrounding hash maps; hashing; and their close relative, the set; are described in detail. Chapter 7, Collections in Rust, attempts to connect to the Rust programmer's daily life, going into the details of the Rust std::collections library, which contains the various data structures provided by the Rust standard library. Chapter 8, Algorithm Evaluation, teaches you how to evaluate and compare algorithms. Chapter 9, Ordering Things, will look at sorting values, an important task in programming—this chapter uncovers how that can be done quickly and safely. Chapter 10, Finding Stuff, moves onto searching, which is especially important if there is no fundamental data structure to support it. In these cases, we use algorithms to be able to quickly find what we are looking for. Chapter 11, Random and Combinatorial, is where we will see that, outside of sorting and searching,