GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
PROPERTIES OF APPROXIMATION BY SEQUENCES OF LINEAR POSITIVE OPERATOR 2/6311305
Course Title: PROPERTIES OF APPROXIMATION BY SEQUENCES OF LINEAR POSITIVE OPERATOR 2
Credits 3 ECTS 7.5
Course Semester 1 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
having to ability for research in approximation theory
Learning Korovkin type approximation by linear positive operators
Applicable the weighted approximation theorems
Learning the properties of approximation of the linear positive operators involving orthogonal polynomials
Learning the properties of approximation of GBS operators
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 --WEEKLY SCHEDULE
1. Week  Korovkin type theorems for a sequences of linear positive operators acting in the weighted spaces of continuous functions defined on unbounded sets,
2. Week  Korovkin type theorems for a sequences of linear positive operators acting in the Lp and weighted Lp spaces
3. Week  Approximation by Durrmeyer type, Szasz-Beta type and Phillips operators and mixed summation type operators
4. Week   Obtaining the Rate of Convergence and degree of approximation
5. Week  King type generalizations of linear positive operators
6. Week  Jain type Generalization of linear positive operators
7. Week  Applications and solutions of problems
8. Week  approximation by Szasz operators involving Apppell polynomials
9. Week  approximation by Szasz operators involving Charlier polynomials
10. Week  approximation by Szasz operators involving Sheffer and Brenke polynomials
11. Week  The convergnece properties of sequences of linear positive operators in the space of continuous functions of several variables.
12. Week  GBS (Generalized Boolean Sum) type of linear pısitive operators in two variables.
13. Week  degree of approximation of GBS operators in mixed modulus of convergence
14. Week  Solutions of problems
15. Week  
16. Week  
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
20
 Assignment
3
20
 Application
0
0
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
40
 Percentage of Final Exam to Total Score  
60
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
 Reading Tasks
14
4
56
 Searching in Internet and Library
14
3
42
 Material Design and Implementation
0
 Report Preparing
0
 Preparing a Presentation
0
 Presentation
0
 Midterm Exam and Preperation for Midterm Exam
1
14
14
 Final Exam and Preperation for Final Exam
1
22
22
 Other (should be emphasized)
5
2
10
 TOTAL WORKLOAD: 
186
 TOTAL WORKLOAD / 25: 
7.44
 Course Credit (ECTS): 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1To be able to develop their knowledge of theory and applications at master degree depending on the competencies acquired in undergraduate level.X
2To be able to recognize different problems encountered in mathematics and to be able to make studies for their solutions.X
3To be able to formulate new solutions with scientific methods mostly based on analysis and synthesis.X
4To be able to carry out his/her works either independently or in groups within a project considering his/her knowledge on the field he/she works in a critical approach.X
5To be able to continue his/her works considering social, scientific and ethical values.X
6To be able to follow scientific and social developments related to his/her field.X
7To be able to carry out his/her works within the framework of quality management, workplace safety and environmental awareness and to be able to present systematically his/her works using various methods like written, oral or visual.X
8To be able to use methods of accessing knowledge effectively in accordance with ethical values.X
9To be able to use knowledge in other disciplines by combining it with mathematical information.X
10To be able to make activities in the awareness of need for lifelong learning.X
11To be able to make connections between mathematical and social concepts and produce solutions with scientific methods.X
12To be able to use his/her mathematical knowledge in technology.X
 -- NAME OF LECTURER(S)
   (Prof.Dr. NURHAYAT İSPİR 2. Prof. Dr. H. Gül İNCE İLARSLAN)
 -- WEB SITE(S) OF LECTURER(S)
   (websitem.gazi.edu.tr/site/nispir www.websitem.gazi.edu.tr/ince)
 -- EMAIL(S) OF LECTURER(S)
   (nispir@gazi.edu.tr ince@gazi.edu.tr )