čs en |

Algorithms for Engineering Informatics (E371014)

Departments: | ústav přístrojové a řídící techniky (12110) | ||

Abbreviation: | Approved: | 24.02.2009 | |

Valid until: | ?? | Range: | 2P+2C |

Semestr: | L,Z | Credits: | 5 |

Completion: | Z,ZK | Language: | EN |

Annotation

Basic introduction into Java (tasks can be solved in any language). Algorithms with numbers - Divide-and-conquer algorithms, Recurrence relations, the fast Fourier transform. Big-O notation. Sorting algorithms - Bubble sort, Insert sort, Selection sort, Heap sort, Quick sort, Mergesort. Graphs - Depth-fit search in undirected graph, Depth-fit search in directed graphs, Strongly connected components. Paths in graphs - Distances, Breadth-first search, Lengths on edges, Dijkstra's algorithm, Priority queue implementations, Shortest paths in the presence of negative edges, Shortest paths in dags. Greedy algorithms - Minimum spanning trees, Huffman encoding.

Teacher's

Ing. Vladimír Hlaváč Ph.D.

Letní 2019/2020

Ing. Vladimír Hlaváč Ph.D.

Letní 2018/2019

Ing. Vladimír Hlaváč Ph.D.

Letní 2017/2018

Structure

Introduction into Java programming (all examples in Java).

Theory of algorithms. Complexity of algorithms. Big-O notation.

Mathematical algorithms - multiplication of two matrices, the greatest common divisor, the least common multiple ( LCM ) , Euclid's algorithm.

Factorial, recursion, factorization.

Divide-and-conquer algorithms, recurrence relations, the fast Fourier transform.

Sorting algorithms - bubble sort, combo sort, insert sort, selection sort, heap sort, quick sort, mergesort. Counting sort.

Data structures, linked lists (stack, circular queue), trees (binary, AVL, red-black; B-trees).

Graphs and graph algorithms - terminology, notation , theory, breadth-first search , BFS, depth-first search , DFS, minimum spanning tree.

Paths in graphs - distances, breadth-first search, lengths on edges, Dijkstra's algorithm, priority queue implementations, shortest paths in the presence of negative edges, shortest paths in dags. Greedy algorithms - minimum spanning trees, Huffman encoding, Horn formulas.

Cryptography - historical ciphers, search primes, factorization, symmetric ciphers.

Theory of algorithms. Complexity of algorithms. Big-O notation.

Mathematical algorithms - multiplication of two matrices, the greatest common divisor, the least common multiple ( LCM ) , Euclid's algorithm.

Factorial, recursion, factorization.

Divide-and-conquer algorithms, recurrence relations, the fast Fourier transform.

Sorting algorithms - bubble sort, combo sort, insert sort, selection sort, heap sort, quick sort, mergesort. Counting sort.

Data structures, linked lists (stack, circular queue), trees (binary, AVL, red-black; B-trees).

Graphs and graph algorithms - terminology, notation , theory, breadth-first search , BFS, depth-first search , DFS, minimum spanning tree.

Paths in graphs - distances, breadth-first search, lengths on edges, Dijkstra's algorithm, priority queue implementations, shortest paths in the presence of negative edges, shortest paths in dags. Greedy algorithms - minimum spanning trees, Huffman encoding, Horn formulas.

Cryptography - historical ciphers, search primes, factorization, symmetric ciphers.

Structure of tutorial

Introduction into running applications in 308 laboratory, students' accounts.

Simple application. Constants. Simple types, structured types incl. arrays, records, sets, files. Variables. Basics of programming language.

Sorting. Handling events and exceptions.

Printing from Java applications, I/O operations.

Dynamic data structures: stack, queue, linked list, tree.

Binary tree, AVL tree, B-tree.

Graph algorithms.

Each student will be submitted 3 practical excercises to solve, in the range of lectures. Their solutions will create part of the final classification.

Simple application. Constants. Simple types, structured types incl. arrays, records, sets, files. Variables. Basics of programming language.

Sorting. Handling events and exceptions.

Printing from Java applications, I/O operations.

Dynamic data structures: stack, queue, linked list, tree.

Binary tree, AVL tree, B-tree.

Graph algorithms.

Each student will be submitted 3 practical excercises to solve, in the range of lectures. Their solutions will create part of the final classification.

Literarture

Study materials including lecture slides and preparations are provided by lecturer.

Requirements

The course strongly assumes prior knowledge on level of course Algorithms 1.

For the Exams: knowledge prescribed in lectures. The exam has a practical and oral parts. The practical part of the exam - write and debug a simple program on given task.

For Assessment, the student receies three tasks to program.

For the Exams: knowledge prescribed in lectures. The exam has a practical and oral parts. The practical part of the exam - write and debug a simple program on given task.

For Assessment, the student receies three tasks to program.

Keywords

algorithms, searching, sorting, linked list, tree, recurrence, graphs

data online/KOS/FS :: [Helpdesk] (hlášení problémů) :: [Reload] [Print] [Print wide] © 2011-2017 [CPS] v3.7 (master/180e4e5a/2019-10-09/02:51)