Course detail

Selected Chapters on Algorithms

FIT-VKDAcad. year: 2019/2020

The subject is pointed to advances methods of analysis techniques in areas of dynamic programming, advanced data structures like B-Trees, Binomial Trees and Heaps, Fibonacci Heaps, Red-Black Trees, Skip-Lists, Splay Trees.

Language of instruction

Czech

Mode of study

Not applicable.

Guarantor

prof. Ing. Jan M. Honzík, CSc.

Department

Department of Information Systems (UIFS)

Learning outcomes of the course unit

  • Student shows the creative capabilities in edvanced algoritmhs on the doctoral level in project like woek

 

  • Student shows high quality presentation of the results of the project assigned

Prerequisites

  • Knowledge of the algorithmization on the master degree level 

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

Passing the presentation of the project assigned

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

To command the behaviour of the advanced algorithms and data structures. To be acquainted with their fatures, conplexity and applications.

Specification of controlled education, way of implementation and compensation for absences

Not applicable.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

Cormen,T.H., Leiserson,C.E.,Rivest,R.L.: Introduction to Algorithms. MIT Press, Cambridge, Massachusetts, London, England 1990.

Classification of course in study plans

  • Programme CSE-PHD-4 Doctoral

    branch DVI4 , 0 year of study, summer semester, elective

  • Programme CSE-PHD-4 Doctoral

    branch DVI4 , 0 year of study, summer semester, elective

Type of course unit

 

Lecture

39 hod., optionally

Teacher / Lecturer

prof. Ing. Jan M. Honzík, CSc.

Syllabus

  • Recursion: The substitution method, the iteration method, the master method, proof of the master method
  • Counting and probability
  • Dynamic programming
  • Greedy algorithms
  • Medians and Order Statistics
  • Red-Black Trees
  • Splay Tree
  • Skip-Lists
  • B-Trees
  • Binomial Tree
  • Binomial Heap
  • Fibonacci Heap
  • Polynomial and FFT

Guided consultation in combined form of studies

26 hod., optionally

Teacher / Lecturer

prof. Ing. Jan M. Honzík, CSc.