TAILIEUCHUNG - Lecture Algorithms and data structures: Chapter 2 - Searching

This topic reviews the basic mathematics required in this course: A justification for a mathematical framework, the ceiling and floor functions, L’Hôpital’s rule, logarithms, arithmetic and other polynomial series, geometric series, recurrence relations, weighted averages, combinations. | Review 1 Arrays & Strings Array Array Elements Accessing array elements Declaring an array Initializing an array Two-dimensional Array Array of Structure String Array of Strings Examples Searching Introduction to Searching External and Internal Searching Types of Searching Linear or sequential search Binary Search Algorithms for Linear Search Algorithms for Binary Search 2 Introduction Information retrieval is one of the most important applications of computers We are given a name and are asked for an associated telephone listing We are given an account number and are asked for the transactions occurring in that account We are given an employee name or number and are asked for the employee records 3 Introduction Information retrieval is one of the most important applications of computers We are given a name and are asked for an associated telephone listing We are given an account number and are asked for the transactions occurring in that account We are given an employee name or number and are asked for the employee records 4 Searching is a process of checking and finding an element from a list of elements If we want to find the presence of an element “data” in A, then we have to search for it The search is successful if data does appear in A and unsuccessful otherwise A question you should always ask when selecting a search algorithm is “How fast does the search have to be?” The reason is that, in general, the faster the algorithm is, the more complex it is. Bottom line: you don’t always need to use or should use the fastest algorithm 5 Key In these examples, we are given one piece of information, which we shall call a key We are asked to find a record that contains other information associated with the key We shall allow both the possibility that there is more than one record with the same key and that there is no record with the given key 6 Records and their keys 7 Analysis Searching for the keys that locate records is often the most time-consuming action in a .

• Cơ sở dữ liệu
• Algorithm analysis
• Graph algorithms
• Design techniques
• Data structures
• Lecture Algorithms and data structures
• Algorithm analysis
• Design techniques
• Cấu trúc dữ liệu
• Algorithm analysis in C++
• The disjoint sets class
• Algorithm design techniques
• Amortized analysis
• Advanced data structures
• Advanced Algorithms Analysis and Design
• Lecture Advanced Algorithms Analysis and Design
• Bài giảng Phân tích và thiết kế thuật toán nâng cao
• The Floyd Warshall algorithm
• Johnson’s algorithm
• Bellman Ford algorithm
• Algorithm design
• Lecture Algorithm design
• Computational tractability
• Asymptotic order of growth
• Polynomial running time
• Dynamic programming
• Hirschbergs algorithm
• Greedy Algorithms
• Dijkstras algorithm
• Minimum spanning trees
• Network flow
• Ford Fulkerson algorithm
• Max flow min cut theorem
• Analysis in C++
• A general overview
• Extendible hashing
• Hash tables in the standard library
• Performance analysis of a sugar plant using genetic algorithm
• Optimization of crystallization system of a sugar plant using genetic algorithm
• A sugar plant using genetic algorithm
• Refining system fails
• The crystallization system includes crystallization units
• Local search
• Gradient descent
• Metropolis algorithm
• Analysis of Algorithm
• Incorrect algorithms
• Analyzing an algorithm
• nalyzing an algorithm
• The correct output
• Communication bandwidth
• Computational time
• A practical introduction
• Mathematical preliminaries
• Binary trees
• Non binary trees
• Internal sorting
• Graph search
• Graph connectivity
• Graph traversal
• Coin changing
• Optimal caching
• Counting inversions
• Closest pair of points
• Randomized quicksort
• Master theorem
• Integer multiplication
• Matrix multiplication
• Weighted interval scheduling
• Knapsack problem
• Bipartite matching
• Disjoint paths
• Assignment problem
• Input queued switching
• Poly time reductions
• Constraint satisfaction problems
• Graph coloring
• Decision problems
• NP complete
• Nondeterministic polynomial
• PSPACE complexity class
• Quantified satisfiability
• PSPACE complete
• Vertex covers
• Bipartite graphs
• Limits of tractability
• Approximation Algorithms
• Vertex cover
• Randomized Algorithms
• Contention resolution
• Linearity of expectation
• Performance analysis of a real time adaptive prediction algorithm
• Real time adaptive prediction algorithm for traffic congestion
• Lower Mean Square Error
• The actual traffic congestion states