1 Preliminaries 3 1.1 A Bit of History 4 1.2 Introduction 7 1.3 Motivation 8 1.3.1 Optics 8 1.3.2 Shape of a Liquid Drop 10 1.3.3 Optimization of a River-Crossing Trajectory 12 1.3.4 Summary 14 1.4 Extrema of Functions 14 1.5 Constrained Extrema and Lagrange Multipliers 17 1.6 Integration by Parts 20 1.7 Fundamental Lemma of the Calculus of Variations 21 1.8 Adjoint and Self-Adjoint Differential Operators 22 Exercises 26 2 Calculus of Variations 28 2.1 Functionals of One Independent Variable 29 2.1.1 Functional Derivative 30 2.1.2 Derivation of Euler’s Equation 31 2.1.3 Variational Notation 33 2.1.4 Special Cases of Euler’s Equation 37 2.2 Natural Boundary Conditions 44 2.3 Variable End Points 53 2.4 Higher-Order Derivatives 56 2.5 Functionals of Two Independent Variables 56 2.5.1 Euler’s Equation 57 2.5.2 Minimal Surfaces 61 2.5.3 Dirichlet Problem 62 vii viii Contents 2.6 Functionals of Two Dependent Variables 64 2.7 Constrained Functionals 66 2.7.1 Integral Constraints 66 2.7.2 Sturm-Liouville Problems 74 2.7.3 Algebraic and Differential Constraints 76 2.8 Summary of Euler Equations 80 Exercises 81 3 Rayleigh-Ritz, Galerkin, and Finite-Element Methods 90 3.1 Rayleigh-Ritz Method 91 3.1.1 Basic Procedure 91 3.1.2 Self-Adjoint Differential Operators 94 3.1.3 Estimating Eigenvalues of Differential Operators 96 3.2 Galerkin Method 100 3.3 Finite-Element Methods 103 3.3.1 Rayleigh-Ritz–Based Finite-Element Method 104 3.3.2 Finite-Element Methods in Multidimensions 109 Exercises 110 P A R T I I P H Y S I C A L A P P L I C A T I O N S 115 4 Hamilton’s Principle 117 4.1 Hamilton’s Principle for Discrete Systems 118 4.2 Hamilton’s Principle for Continuous Systems 128 4.3 Euler-Lagrange Equations 131 4.4 Invariance of the Euler-Lagrange Equations 136 4.5 Derivation of Hamilton’s Principle from the First Law of Thermodynamics 137 4.6 Conservation of Mechanical Energy and the Hamiltonian 141 4.7 Noether’s Theorem – Connection Between Conservation Laws and Symmetries in Hamil

这是关于优化算法的电子书，高清，最新版本，经典著作，英文版

英文版的汽车软件工程-原理.过程.方法.工具，原汁原味。

Software Engineering, 8th edition, Ian Sommerville 2006 全英文PDF版课件 第二版

需要读者有控制论的基础，是一本很系统的涵盖控制领域的所有命题 工程控制论.Engineering.Cybernetics[英文原版]钱学森

ees（engineering equation solver）资料 ，英语原文

本文档为《控制系统工程 6th(Norman S. Nise) Control Systems Engineering》课后习题答案，可适用于高等教育领域

代理模型经典入门书籍，高清含有目录标签。非常不错的阅读体验。

Produce a fully functioning Intelligent System that leverages machine learning and data from user interactions to improve over time and achieve success. This book teaches you how to build an Intelligent System from end to end and leverage machine learning in practice. You will understand how to apply your existing skills in software engineering, data science, machine learning, management, and program management to produce working systems. Building Intelligent Systems is based on more than a decade of experience building Internet-scale Intelligent Systems that have hundreds of millions of user interactions per day in some of the largest and most important software systems in the world. What You'll Learn Understand the concept of an Intelligent System: What it is good for, when you need one, and how to set it up for success Design an intelligent user experience: Achieve your objectives and produce data to help make the Intelligent System better over time Implement an Intelligent System: Execute, manage, and measure Intelligent Systems in practice Create intelligence: Use different approaches, including machine learning Orchestrate an Intelligent System: Bring the parts together throughout its life cycle and achieve the impact you want This Book Is For Software engineers, machine learning practitioners, and technical managers who want to build effective intelligent systems. Table of Contents Part I: Approaching an Intelligent Systems Project Chapter 1: Introducing Intelligent Systems Chapter 2: Knowing When to Use Intelligent Systems Chapter 3: A Brief Refresher on Working with Data Chapter 4: Defining the Intelligent System’s Goals Part II: Intelligent Experiences Chapter 5: The Components of Intelligent Experiences Chapter 6: Why Creating Intelligent Experiences Is Hard Chapter 7: Balancing Intelligent Experiences Chapter 8: Modes of Intelligent Interaction Chapter 9: Getting Data from Experience Chapter 10: Verifying Intelligent Experiences Part III: Implement