PROGRAMMING with MATLAB

AIM

Equipping the ability to perform data analysis, numerical computing, algorithm development, and modelling and simulation of complex systems. Solving engineering problems, automating tasks, and applying advanced techniques through specialized toolboxes, preparing individuals for real-world technical challenges for academia and industry.

CONTENT

This course contains; Basics of getting, installing, and running Matlab, introducing MATLAB Environment (IDE), some important commands, pre-defined variables, special characters, mathematical operators, input and output, creating, saving and running scripts.,Arrays, array-related MATLAB built-in functions, adding and removing elements from an array, finding specific elements in an array, array operations, mathematical operations on arrays, plotting arrays.,Matrices, matrix-related MATLAB built-in functions, adding and removing elements, rows and columns, finding specific elements in a matrix, matrix operations, mathematical operations on matrices, concatenation of matrices, plotting matrices.,Some important MATLAB built-in functions.,Strings, string arrays, basic string operations, concatenation, indexing, string functions, differences between strings and character arrays.,Plotting, plot customization (color, line style, markers), multiple plots, 3D Plotting, saving plots in different formats, figure properties.,General overview.,If-Else Statement, multiple conditions, logical conditions, relational operators, logical operators, nested If statements, If with vectors and matrices. Switch-Case Statement, multiple cases, the otherwise block evaluating expressions in case.,For-While Loops, looping over arrays and matrices, nested for loops, preallocating arrays in loops, infinite loops, breaking out of loops, using continue in loops, looping until a condition is met, efficient looping with vectorization.,Functions, defining inputs and outputs, calling a function, function handle, anonymous functions, variable number of inputs and outputs, local and global variables, recursion, using built-in functions.,Installing and Using Toolboxes, Symbolic Math Toolbox, creating symbolic variables, symbolic expressions, basic operations.,Using Live Editor with Symbolic Math Toolbox, differentiation, integration, solving equations, simplifying expressions, substitution, numerical evaluation, plotting symbolic expressions.,Optimization Toolbox and Fuzzy System Toolbox.,General overview..

1. 1

   Distinct MATLAB basics.

   Taught by: Mastery Learning, Discussion Method, Demonstration Method, Problem Solving Method, Case Study Method, Self Study Method, Question - Answer Technique, Experimental Technique, Simulation Technique, Problem Baded Learning Model, Computer-Internet Supported Instruction, Inquiry-Based Learning, Cooperative Learning, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Short Answer Exam, Multiple-Choice Exam, Homework, Quiz, Simulation-Based Evaluation

2. 2

   Model an engineering problem in MATLAB.

   Taught by: Mastery Learning, Discussion Method, Demonstration Method, Problem Solving Method, Case Study Method, Self Study Method, Question - Answer Technique, Experimental Technique, Simulation Technique, Problem Baded Learning Model, Computer-Internet Supported Instruction, Inquiry-Based Learning, Cooperative Learning, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Short Answer Exam, Multiple-Choice Exam, Homework, Quiz, Simulation-Based Evaluation

3. 3

   Solve the modeled problem, using special toolkits for this.

   Taught by: Mastery Learning, Discussion Method, Demonstration Method, Problem Solving Method, Case Study Method, Self Study Method, Question - Answer Technique, Experimental Technique, Simulation Technique, Problem Baded Learning Model, Computer-Internet Supported Instruction, Inquiry-Based Learning, Cooperative Learning, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Short Answer Exam, Multiple-Choice Exam, Homework, Quiz, Simulation-Based Evaluation

4. 4

   Perform modeling and simulation.

   Taught by: Mastery Learning, Discussion Method, Demonstration Method, Problem Solving Method, Case Study Method, Self Study Method, Question - Answer Technique, Experimental Technique, Simulation Technique, Problem Baded Learning Model, Computer-Internet Supported Instruction, Inquiry-Based Learning, Cooperative Learning, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Short Answer Exam, Multiple-Choice Exam, Homework, Quiz, Simulation-Based Evaluation

5. 5

   Perform data analysis and visualization.

   Taught by: Mastery Learning, Discussion Method, Demonstration Method, Problem Solving Method, Case Study Method, Self Study Method, Question - Answer Technique, Experimental Technique, Simulation Technique, Problem Baded Learning Model, Computer-Internet Supported Instruction, Inquiry-Based Learning, Cooperative Learning, Experiential Learning, Lecture Method · Assessed by: Traditional Written Exam, Short Answer Exam, Multiple-Choice Exam, Homework, Quiz, Simulation-Based Evaluation

WEEKLY PLAN

1. WEEK 1

   Basics of getting, installing, and running Matlab, introducing MATLAB Environment (IDE), some important commands, pre-defined variables, special characters, mathematical operators, input and output, creating, saving and running scripts.

   Preparation: Previewing book and lecture notes

2. WEEK 2

   Arrays, array-related MATLAB built-in functions, adding and removing elements from an array, finding specific elements in an array, array operations, mathematical operations on arrays, plotting arrays.

   Preparation: Previewing book and lecture notes

3. WEEK 3

   Matrices, matrix-related MATLAB built-in functions, adding and removing elements, rows and columns, finding specific elements in a matrix, matrix operations, mathematical operations on matrices, concatenation of matrices, plotting matrices.

   Preparation: Previewing book and lecture notes

4. WEEK 4

   Some important MATLAB built-in functions.

   Preparation: Previewing book and lecture notes

5. WEEK 5

   Strings, string arrays, basic string operations, concatenation, indexing, string functions, differences between strings and character arrays.

   Preparation: Previewing book and lecture notes

6. WEEK 6

   Plotting, plot customization (color, line style, markers), multiple plots, 3D Plotting, saving plots in different formats, figure properties.

   Preparation: Previewing book and lecture notes

7. WEEK 7

   General overview.

   Preparation: Previewing book and lecture notes

8. WEEK 8

   If-Else Statement, multiple conditions, logical conditions, relational operators, logical operators, nested If statements, If with vectors and matrices. Switch-Case Statement, multiple cases, the otherwise block evaluating expressions in case.

   Preparation: Previewing book and lecture notes

9. WEEK 9

   For-While Loops, looping over arrays and matrices, nested for loops, preallocating arrays in loops, infinite loops, breaking out of loops, using continue in loops, looping until a condition is met, efficient looping with vectorization.

   Preparation: Previewing book and lecture notes

10. WEEK 10

    Functions, defining inputs and outputs, calling a function, function handle, anonymous functions, variable number of inputs and outputs, local and global variables, recursion, using built-in functions.

    Preparation: Previewing book and lecture notes

11. WEEK 11

    Installing and Using Toolboxes, Symbolic Math Toolbox, creating symbolic variables, symbolic expressions, basic operations.

    Preparation: Previewing book and lecture notes

12. WEEK 12

    Using Live Editor with Symbolic Math Toolbox, differentiation, integration, solving equations, simplifying expressions, substitution, numerical evaluation, plotting symbolic expressions.

    Preparation: Previewing book and lecture notes

13. WEEK 13

    Optimization Toolbox and Fuzzy System Toolbox.

    Preparation: Previewing book and lecture notes

14. WEEK 14

    General overview.

    Preparation: Previewing book and lecture notes

ASSESSMENT

• Rate of Midterm Exam to Success30%
• Rate of Final Exam to Success70%

WORKLOAD

READING

• William J. Palm, 2005, Introduction to Matlab 7 for Engineers, Mc Graw Hill.Brian H. Hahn, Daniel T. Valentine, 2017, Essential MATLAB for Engineers and Scientists, Academic Press
• Brian H. Hahn, Daniel T. Valentine, 2017, Essential MATLAB for Engineers and Scientists, Academic Press

TEACHING STAFF

• Assoc.Prof. Atakan MANGIRCOORDINATOR
• Res.Assist. Recep Akif TAŞÇI
• Prof.Dr. Mehmet Kemal ÖZDEMİR