Table of Contents Section I: Introduction to Embedded Systems Chapter 1: A Systems Engineering Approach to Embedded Systems Design Chapter 2: Know Your Standards Section II: Embedded Hardware Chapter 3: Embedded Hardware Building Blocks and the Embedded Board Chapter 4: Embedded Processors Chapter 5: Board Memory Chapter 6: Board I/O (Input/Output) Chapter 7: Board Buses Section III: Embedded Software Introduction Chapter 8: Device Drivers Chapter 9: Embedded Operating Systems Chapter 10: Middleware and Application Software Section IV: Putting It All Together: Design and Development Chapter 11: Defining the System-Creating the Architecture and Documenting the Design Chapter 12: The Final Phases of Embedded Design: Implementation and Testing Appendix A: Projects and Exercises Appendix B: Schematic Symbols Appendix C: Acronyms and Abbreviations Appendix D: Glossary 《嵌入式系统架构》是为工程师和程序员们提供的一本全面的指导书籍，书中深入介绍了嵌入式系统设计的方方面面，内容涵盖了从嵌入式硬件和软件基础知识到设计和开发的实践技巧。本部分将详细阐述书中涉及的知识点。 **嵌入式系统设计的方法论** 书中第一部分“嵌入式系统的引言”深入探讨了系统工程方法在嵌入式系统设计中的应用。系统工程方法要求工程师在设计之初就需要有全面的理解，明确目标和约束条件，并在项目实施过程中考虑整个系统的生命周期。这部分内容强调了对系统进行全面分析的重要性，并提出了定义系统、创建架构和记录设计文档的方法。 **嵌入式硬件基础** 在嵌入式硬件方面，书中涉及了嵌入式硬件构建块、嵌入式处理器、板级存储器、I/O（输入/输出）接口和板级总线技术等内容。这部分知识点不仅包括了硬件组件的基本概念和工作原理，还包括了如何在设计中选择和使用这些组件，以及它们在嵌入式系统中如何协同工作。 **嵌入式软件介绍** 在嵌入式软件方面，书中介绍了设备驱动程序、嵌入式操作系统、中间件以及应用软件等关键内容。设备驱动程序是软件和硬件之间的桥梁，能够控制硬件设备的行为。而嵌入式操作系统提供了运行应用软件所必须的环境，使得多个软件组件能够在有限的资源下高效地运行。中间件则起到了简化开发过程、提供通用功能的作用，使得应用软件开发更加专注于业务逻辑本身。 **系统集成：设计与开发** 在设计和开发部分，书中指出了在定义了系统架构之后，最终的实施和测试阶段是嵌入式设计中不可或缺的环节。本部分将指导读者如何将各个硬件和软件组件整合成一个完整的系统，并进行必要的测试来确保系统的稳定性和性能。 **附录** 书中的附录部分提供了项目和练习，以及与电路设计相关的符号说明、缩写词和专业术语表。这些材料有助于读者更好地理解和应用书中的知识，也能够通过实际操作来加强学习。 **版权声明和免责声明** 书中的版权声明部分强调，尽管知识和最佳实践在不断更新和变化，但书中的材料、信息和方法都受到版权法的保护。读者在使用这些信息时应当遵守相应的法规和准则，同时，出版社和作者不对由于使用本书中的信息所引起的任何形式的责任和损失负责。 本书《嵌入式系统架构》是工程师和程序员在嵌入式系统领域中的一个重要参考资源。通过对系统设计、硬件基础、软件开发以及最终的设计实施和测试等关键知识的讲解，本教材对嵌入式系统开发的各个环节都提供了深入而全面的指导。通过学习本书，读者能够全面掌握嵌入式系统的开发流程，提升设计和实施嵌入式系统的能力。

Through exposure to the news and social media, you are probably aware of the fact that machine learning has become one of the most exciting technologies of our time and age. Large companies, such as Google, Facebook, Apple, Amazon, and IBM, heavily invest in machine learning research and applications for good reasons. While it may seem that machine learning has become the buzzword of our time and age, it is certainly not a fad. This exciting field opens the way to new possibilities and has become indispensable to our daily lives. This is evident in talking to the voice assistant on our smartphones, recommending the right product for our customers, preventing credit card fraud, filtering out spam from our email inboxes, detecting and diagnosing medical diseases, the list goes on and on. If you want to become a machine learning practitioner, a better problem solver, or maybe even consider a career in machine learning research, then this book is for you. However, for a novice, the theoretical concepts behind machine learning can be quite overwhelming. Many practical books have been published in recent years that will help you get started in machine learning by implementing powerful learning algorithms. Getting exposed to practical code examples and working through example applications of machine learning are a great way to dive into this field. Concrete examples help illustrate the broader concepts by putting the learned material directly into action. However, remember that with great power comes great responsibility! In addition to offering a hands-on experience with machine learning using the Python programming languages and Python-based machine learning libraries, this book introduces the mathematical concepts behind machine learning algorithms, which is essential for using machine learning successfully. Thus, this book is different from a purely practical book; it is a book that discusses the necessary details regarding machine learning concepts and offers intuitive yet informative explanations of how machine learning algorithms work, how to use them, and most importantly, how to avoid the most common pitfalls. Currently, if you type "machine learning" as a search term in Google Scholar, it returns an overwhelmingly large number of publications—1,800,000. Of course, we cannot discuss the nitty-gritty of all the different algorithms and applications that have emerged in the last 60 years. However, in this book, we will embark on an exciting journey that covers all the essential topics and concepts to give you a head start in this field. If you find that your thirst for knowledge is not satisfied, this book references many useful resources that can be used to follow up on the essential breakthroughs in this field. If you have already studied machine learning theory in detail, this book will show you how to put your knowledge into practice. If you have used machine learning techniques before and want to gain more insight into how machine learning actually works, this book is for you. Don't worry if you are completely new to the machine learning field; you have even more reason to be excited. Here is a promise that machine learning will change the way you think about the problems you want to solve and will show you how to tackle them by unlocking the power of data. Before we dive deeper into the machine learning field, let's answer your most important question, "Why Python?" The answer is simple: it is powerful yet very accessible. Python has become the most popular programming language for data science because it allows us to forget about the tedious parts of programming and offers us an environment where we can quickly jot down our ideas and put concepts directly into action. We, the authors, can truly say that the study of machine learning has made us better scientists, thinkers, and problem solvers. In this book, we want to share this knowledge with you. Knowledge is gained by learning. The key is our enthusiasm, and the real mastery of skills can only be achieved by practice. The road ahead may be bumpy on occasions and some topics may be more challenging than others, but we hope that you will embrace this opportunity and focus on the reward. Remember that we are on this journey together, and throughout this book, we will add many powerful techniques to your arsenal that will help us solve even the toughest problems the data-driven way.

深度强化学习是一种结合了强化学习和深度学习的智能学习方法，它通过模拟人类的学习方式，使得智能体能够在不确定的环境中进行决策和学习，以实现最大化的累积奖励。在最新的《Deep Reinforcement Learning with Python, 2nd Edition》一书中，作者Sanghi Nimish深入探讨了深度强化学习的理论基础和实际应用，特别是在聊天机器人和大型语言模型中的应用。 该书的第二版专注于介绍强化学习中的人工智能（AI）训练技术，即所谓的强化学习的反馈（Reinforcement Learning from Human Feedback，简称RLHF）。这种技术能够通过人类的反馈来训练和改进AI系统，尤其在聊天机器人和大型语言模型的训练中发挥着重要作用。本书从基础的深度强化学习概念出发，逐步深入到复杂的人工智能训练领域。 书中不仅详细介绍了深度强化学习的基本概念和核心算法，例如Q学习、策略梯度方法、Actor-Critic方法等，还深入讲解了如何将这些算法应用于不同的问题和环境。Sanghi Nimish还讨论了深度强化学习在现代人工智能应用中的挑战和解决方案，比如如何处理高维观测空间和如何提高学习效率。 此外，作者还提供了大量编程实例和案例研究，帮助读者更好地理解和掌握深度强化学习的实现方法。对于希望深入研究深度强化学习，或者希望将其应用于聊天机器人和大型语言模型开发的读者来说，这本书是难得的学习资源。 由于文档中提到本书的版权内容，这表明了这本书是受到版权法保护的。对于本书中提到的商标名称、标志和图片，作者和出版社遵循了编辑式的使用方式，并尊重商标权所有者的利益，且没有侵犯商标的意图。同时，出版社也对本书内容的准确性、完整性不承担法律责任，并对可能出现的错误或遗漏不负责。 在书中，出版社还提到了书中的内容，包括翻译、翻印、插图再利用、朗诵、广播、微缩胶片复制或其他形式的复制，以及信息的传输或存储和检索、电子适应、计算机软件或任何现在已知或将来开发的方法的权利。此外，对于书中的商标名称、商标、服务标记和类似术语，出版社声明这不构成对专有权的主张。 出版社对本书中提供的建议和信息的准确性负责，但不承担任何法律义务。同时，出版社也声明，对于可能出现的错误或遗漏，出版社无法做出保证。出版社对于书中包含的材料也不承担任何明示或暗示的保证。 本书的编辑和出版涉及多位专业人士，例如Apress Media LLC的常务董事Welmoed Spahr，以及编辑Celestin Suresh John、发展编辑James Markham、编辑助理Gryffin Winkler和校对Kezia Ends等，他们共同保证了本书的专业性和高质量。 《Deep Reinforcement Learning with Python, 2nd Edition》是一本全面且实用的深度强化学习学习资源。它不仅提供了理论知识，还注重实践应用，尤其是在AI训练领域中的人类反馈强化学习的最新发展。

《LaTeX伴侣》（第二版）是LaTeX排版系统学习者的一本重要参考书籍。这本书详细地介绍了LaTeX文档的结构、排版工具、页面布局、表格材料、浮动对象的管理、字体和编码以及高等数学排版等多个方面的内容。 书中概述了LaTeX系统的历史和发展现状（Section 1.1）以及如何使用本书（Section 1.3）。接着，它详细阐述了LaTeX文档的基本结构（Chapter 2），包括源文件的结构、章节命令、目录结构以及引用管理等内容（Section 2.1至Section 2.4）。这一部分是学习LaTeX的基础，帮助读者理解如何组织文档内容。 文档排版是LaTeX的主要功能之一，本书在第三章（Chapter 3）和第四章（Chapter 4）中对此进行了详尽介绍。在第三章中，基本格式化工具的使用被重点讲解，涵盖了短语和段落排版、脚注和边注、列表结构、模拟打字文本以及行和列的处理（Section 3.1至Section 3.5）。而第四章则进一步介绍了页面布局的各个方面，包括页面几何尺寸、改变布局、动态页面数据（页码和标志）、页面样式、视觉格式设置以及使用类进行布局（Section 4.1至Section 4.6）。 表格材料（Chapter 5）是LaTeX排版中不可或缺的部分。本书不但介绍了标准LaTeX环境的使用（Section 5.1），还涉及了如何使用array包扩展表格环境（Section 5.2），计算列宽（Section 5.3）、处理多页表格（Section 5.4）、在表格中使用颜色（Section 5.5）以及自定义表格规则和间距（Section 5.6）。此外，书中还讲解了表注的使用（Section 5.8）以及表格材料的应用实例（Section 5.9）。 浮动对象是LaTeX排版的高级特性之一，特别是在处理图表和表格时。第六章（Chapter 6）讲述了如何掌握浮动对象，包括理解浮动参数（Section 6.1）、浮动放置控制（Section 6.2）、扩展LaTeX的浮动概念（Section 6.3）、内联浮动对象（Section 6.4）以及控制浮动标题（Section 6.5）。 LaTeX的强大排版能力同样体现在字体和符号的使用上。第七章（Chapter 7）探讨了LaTeX中的字体和编码，内容包括字体特征的了解（Section 7.2）、在文本和数学环境中使用字体（Section 7.3和Section 7.4）、标准LaTeX字体支持（Section 7.5）、PostScript字体的使用（Section 7.6）、字体包的集合（Section 7.7）、LaTeX符号世界（Section 7.8）、底层接口（Section 7.9）、设置新字体（Section 7.10）以及LaTeX的编码模型和兼容旧文档的包（Section 7.11和Section 7.12）。 在LaTeX排版中，高等数学的排版占有很重要的地位，第八章（Chapter 8）介绍了AMS-LaTeX，这是LaTeX的一个扩展包，专门用于处理数学符号和公式。内容涵盖了高等数学排版入门（Section 8.1）、公式的显示和对齐结构（Section 8.2）以及类似矩阵的环境（Section 8.3）。 整体而言，《LaTeX伴侣》（第二版）这本书为LaTeX用户提供了一个全面的工具箱，无论是初学者还是经验丰富的排版专家，都能从中学到实用的技巧和方法。通过掌握书中介绍的丰富知识点，用户可以更加自信地解决文档排版中遇到的各种问题，并创作出专业的学术论文和书籍。

Fully revised and updated, Pathophysiology Made Incredibly Visual, Second Edition, offers an innovative visual approach to mastering the principles of pathophysiology. Using the Incredibly Easy! approach to learning, which breaks complex concepts into managable pieces of information, the book combines detailed images with clear, concise text to make pathophysiology concepts easy to understand. Hundreds of detailed color photographs, diagrams, charts, and other visual aids clarify essential pathophysiology concepts, and key terms and concept are clearly explained.  Special sections present visual mnemonics and reinforce key points, including a summary of risk factors for each clinical disorder.  ,解压密码 share.weimo.info

Java 9 Concurrency Cookbook Second Edition Java 9 Concurrency Cookbook Second Edition Java 9 Concurrency Cookbook Second Edition

Help for Power Users and Sys Admins It’s simple: if you want to interact deeply with Mac OS X, Linux, and other Unix-like systems, you need to know how to work with the Bash shell. This concise little book puts all of the essential information about Bash right at your fingertips.You’ll quickly find answers to the annoying questions that generally come up when you’re writing shell scripts: What characters do you need to quote? How do you get variable substitution to do exactly what you want? How do you use arrays? Updated for Bash version 4.4, this book has the answers to these and other problems in a format that makes browsing quick and easy.Topics include:,解压密码 share.weimo.info

之前下载的书签是坏的，逐一修复了每个章节的书签链接。 This book is a comprehensive introduction and developer's guide to the Eclipse Modeling Framework (EMF). EMF is a powerful framework and code generation facility for building Java applications based on simple model definitions. Designed to make modeling practical and useful to the mainstream Java programmer, EMF unifies three important technologies: Java, XML, and UML. Models can be defined using a UML modeling tool or an XML Schema, or even by specifying simple annotations on Java interfaces. In this last case, the developer writes just a subset of abstract interfaces that describe the model, and the rest of the code is generated automatically and merged back in.

以下是使用等待统计信息分析SQLServer性能并排除故障的实用指南。学习如何准确地确定查询运行缓慢的原因。测量每个瓶颈所消耗的时间，以便您可以首先集中精力进行最大的改进。此版本被更新，以涵盖查询存储中等待统计信息的分析、CXCONSUMER等待事件以及SQLServer 2019年的最新情况。无论您是刚刚开始等待统计，还是已经熟悉这些统计信息，这本书提供了关于等待统计信息是如何生成的以及它们对SQL Server实例的性能意味着什么的更深入的理解。PRO SQL Server 2019等待统计不仅限于最常见的等待类型，还包括更复杂和更具性能威胁的等待类型。您将了解每个查询等待统计信息和基于会话的等待统计信息，以及它们各自可以帮助您解决的问题类型。不同的等待类型按其影响区域分类，包括CPU、IO、Lock等。本书提供了明确的示例，帮助您了解具体的等待时间增加或减少的原因和方式，以及它们如何影响SQLServer的性能。读完这本书后，你将不希望没有等待统计数据提供的有价值的信息，这些信息是关于您应该将有限的调优时间用于最大限度地提高性能和对您的业务的价值。

用wait statistics分析诊断 SQL Server 性能。找出查询慢的原因。对每个瓶颈计时以专注于做出最大的改进。这本书已经更新，讲述在Query Store分析wait statistics , CXCONSUMER wait 事件, 以及SQL Server 2019最新进展.