Pattern Recognition 



Course Activity:

Course unit type:

Content:


A. General competences 
PB  01. Intellectual and cognitive capacities Explanation PB – 01. The student is able to classify objects and phenomena and use corresponding features to describe them PB – 02. Depending on the type of a priori and a posteriori information the student is able to choose and use appropriate methods of recognizing real life objects and phenomena 
B. Professionoriented/ General scientific competences 
Explanation

C. Professionspecific competences 
Linear and nonlinear decision rules, Bayes criterion, Pirson criterion, Wald’s statistical analysis, Boolean algebra methods, simulating modeling. 
D. Scientific competences 
/ Explanation / 
Prerequisites: 
A. Previously required courses 
Mathematical Analysis, Algebra, Theory of Probability and Mathematical Statistics, Discrete Mathematics, Mathematical Logic, Theoretical Basis of Informatics, Geometry, Numerical Methods 
B. Required competences 
Mathematical Analysis: the methods of working with analytical functions, convex analysis, vector analysis, methods of constructing pivotal separating hyper plane. Algebra: the calculation with letters, matrices and special products, solving of equations of the first, second and ndegree, solving of simultaneous equations. The Differential Analysis: finding derivations of the first and second degree and complex derivations, working with integrals of the first degree. Theory of Probability and Statistics: theorem of probability calculation, conditional expectation function, variance, probability distribution of conditional density, the law of large numbers, regression analysis method, statistical criteria. Calculation methods: branchandbound method, set of equations solving methods. Boolean algebra: predicate calculus. 
Educational tools: 
A. Type 

B. Obligatory educational tools 
course book: Methods of Recognition by A. GORELIK, V. SKRIPKIN (both in English and Russian) Mathematical computing systems: Mathcad, Mathlab 
C. Recommended educational tools 
Textbooks:


A. Type 

B. Description 
This course is taught in English or Russian Plenary lectures: 36h = 2h per week during 18 weeks during the first semester. Practical Classes (obliged): 18h = 2h per two weeks during 18 weeks during the first semester. Lab Classes: (obliged): 18h = 2h per 2 weeks during 18 weeks during the first semester. Higher distance education: for this course, an extra syllabus is available, containing guidelines how to study the material in an optimal way. 

A. Type 

B. Description 
Total number of credits: 5 credits 
Teaching support :
Extra course OR: 2h per week during 18 weeks during the first semester. 