 Introduction  Secure state  Security analysis-linear sensitivity analysis method

1 The Role of Algorithms in Computing 2 Getting Started 3 Growth of Functions 4 Divide-and-Conquer 5 Probabilistic Analysis and Randomized Algorithms 6 Heapsort 7 Quicksort 8 Sorting in Linear Time 9 Medians and Order Statistics 10 Elementary Data Structures 11 Hash Tables 12 Binary Search Trees 13 Red-Black Trees 14 Augmenting Data Structures 15 Dynamic Programming 16 Greedy Algorithms 17 Amortized Analysis 18 B-Trees 19 Fibonacci Heaps 20 van Emde Boas Trees 21 Data Structures for Disjoint Sets 22 Elementary Graph Algorithms 23 Minimum Spanning Trees 24 Single-Source Shortest Paths 25 All-Pairs Shortest Paths 26 Maximum Flow 27 Multithreaded Algorithms 28 Matrix Operations 29 Linear Programming 30 Polynomials and the FFT 31 Number-Theoretic Algorithms 32 String Matching 33 Computational Geometry 34 NP-Completeness 35 Approximation Algorithms

CHAPTER ONE:ANALYSIS OF ALGORITHMS CHAPTER TWO:RECURRENCE RELATIONS CHAPTER THREE:GENERATING FUNCTIONS CHAPTER FOUR:ASYMPTOTIC APPROXIMATIONS CHAPTER FIVE:ANALYTIC COMBINATORICS CHAPTER SIX:TREES CHAPTER SEVEN:PERMUTATIONS CHAPTER EIGHT:STRINGS AND TRIES CHAPTER NINE:WORDS AND MAPPINGS

Principles of FDM-TDMA Cellular SIR Analysis Channel Reuse Analysis Spectrum Efficiency Dynamic Channel Allocation Handovers

§0.1 矢量代数（vector analysis） §0.2 微分（differential calculus） §0.3 积分（integral calculus） §0.4 曲线坐标系（curvilinear coordinates） §0.5 Delta 函数（The Dirac Delta function） §0.6 矢量场论（Theory of vector fields）

• 什么是Graphical Model • 定义、示例 • Representation、Inference、Learning • 主题模型与分类 • LSA (Latent Semantic Analysis), 1990 • pLSA (probabilistic Latent Semantic Analysis), 1999 • LDA(Latent Dirichlet Allocation), 2003 • Hierarchical Bayesian model • 主题模型的R语言实现示例

西安电子科技大学：《数据结构与算法分析 Data Structure and Algorithm Analysis》课程教学资源（PPT课件讲稿）06 Algorithm Analysis and Sorting

◼ Cluster Analysis: Basic Concepts ◼ Partitioning Methods ◼ Hierarchical Methods ◼ Density-Based Methods ◼ Grid-Based Methods ◼ Evaluation of Clustering ◼ Summary

I Orienting employees II The training process 2.1 Why the training business is booming 2.2 The 5-step training & development process 2.3 Training and learning III Motivate the learner 3.1 Analyzing training needs 3.2 Task analysis: assessing new employees’ training needs 3.3 Performance analysis: assessing current employees’ training needs IV Traditional training methods V Electronic training VI Managerial development & training VII Evaluating the training effort

❖ H&M Story and Overview ❖ Fast Fashion Market ❖ H&M Main Business Activites ❖ H&M Business Model ❖ H&M market segments and targets ❖ Competitor Analysis ❖ SWOT Analysis ❖ Challenges faced by H&M ❖ H&M Marketing Strategies ❖ H&M Future Development