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| Course Description |
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| Course Name |
: |
Random Variables and Processes for Computer Engineering |
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| Course Code |
: |
CENG-533 |
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| Course Type |
: |
Optional |
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| Level of Course |
: |
Second Cycle |
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| Year of Study |
: |
1 |
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| Course Semester |
: |
Fall (16 Weeks) |
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| ECTS |
: |
6 |
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| Name of Lecturer(s) |
: |
Asst.Prof.Dr. MEHMET FATİH AKAY
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| Learning Outcomes of the Course |
: |
Learns functions of random variable.
Learns the concepts of expected value, variance and moment
Generates a random variable distribution.
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| Mode of Delivery |
: |
Face-to-Face |
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| Prerequisites and Co-Prerequisites |
: |
None |
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| Recommended Optional Programme Components |
: |
None |
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| Aim(s) of Course |
: |
Be associated to the concepts of probability and random processes. |
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| Course Contents |
: |
Probability, conditional probability, Bernoulli trials, the concept of a random variable, distribution and density functions, specific random variables, conditional distributions, functions of one random variable, mean and variance, functions of two random variables, conditional expected values, stochastic processes, systems with stochastic inputs, the power spectrum, discrete-time processes, poisson process. |
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| Language of Instruction |
: |
English |
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| Work Place |
: |
Classroom |
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Course Outline /Schedule (Weekly) Planned Learning Activities |
| Week | Subject | Student's Preliminary Work | Learning Activities and Teaching Methods |
|
1 |
Basics |
Chapter 1 |
Lectures and Demonstration |
|
2 |
Independence and Bernoulli Trials |
Chapter 1 |
Lectures and Demonstration |
|
3 |
Random Variables |
Chapter 2 |
Lectures and Demonstration |
|
4 |
Binomial Random Variable Applications and Conditional
Probability Density Function |
Chapter 2 |
Lectures and Demonstration |
|
5 |
Function of a Random Variable |
Chapter 3 |
Lectures and Demonstration |
|
6 |
Mean, Variance, Moments and Characteristic Functions |
Chapter 3 |
Lectures and Demonstration |
|
7 |
Two Random Variables |
Chapter 4 |
Lectures and Demonstration |
|
8 |
One Function of Two Random Variables |
Chapter 4 |
Lectures and Demonstration |
|
9 |
Two Functions of Two Random Variables |
Chapter 4 |
Lectures and Demonstration |
|
10 |
Joint Moments and Joint Characteristic Functions |
Chapter 4 |
Lectures and Demonstration |
|
11 |
Conditional Expected Values |
Chapter 5 |
Lectures and Demonstration |
|
12 |
Principles of Parameter Estimation |
Chapter 5 |
Lectures and Demonstration |
|
13 |
Examples |
All chapters |
Lectures and Demonstration |
|
14 |
Examples |
All chapters |
Lectures and Demonstration |
|
15 |
Final Exam |
n/a |
n/a |
|
16/17 |
Final Exam |
n/a |
n/a |
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Required Course Resources |
| Resource Type | Resource Name |
| Recommended Course Material(s) |
 Probability, Random Variables and Stochastic Processes, 4th ed. Athanasios Papoluis S. Unnikrishna Pillai
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| |
| Required Course Material(s) | |
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Assessment Methods and Assessment Criteria |
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Semester/Year Assessments |
Number |
Contribution Percentage |
|
Mid-term Exams (Written, Oral, etc.) |
0 |
0 |
|
Homeworks/Projects/Others |
13 |
100 |
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Total |
100 |
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Rate of Semester/Year Assessments to Success |
40 |
| |
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Final Assessments
|
100 |
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Rate of Final Assessments to Success
|
60 |
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Total |
100 |
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| Contribution of the Course to Key Learning Outcomes |
| # | Key Learning Outcome | Contribution* |
|
1 |
Reaches wide and deep knowledge through scientific research in the field of computer engineering, evaluates, implements, and comments. |
3 |
|
2 |
Describes and uses information hidden in limited or missing data in the field of computer engineering by using scientific methods and integrates it with information from various disciplines. |
3 |
|
3 |
Follows new and emerging applications of computer engineering profession, if necessary, examines and learns them |
0 |
|
4 |
Develops methods and applies innovative approaches in order to formulate and solve problems in computer engineering. |
0 |
|
5 |
Proposes new and/or original ideas and methods in the field of computer engineering in developing innovative solutions for designing systems, components or processes. |
0 |
|
6 |
Designs and implements analytical modeling and experimental research and solves the complex situations encountered in this process in the field of Computer Engineering |
4 |
|
7 |
works in multi disciplinary teams and takes a leading role and responsibility. |
0 |
|
8 |
Learns at least one foreign language at the European Language Portfolio B2 level to communicate orally and written |
1 |
|
9 |
Presents his/her research findings systematically and clearly in oral and written forms in national and international meetings. |
0 |
|
10 |
Describes social and environmental implications of engineering practice. |
0 |
|
11 |
Considers social, scientific and ethical values in collection, interpretation and announcement of data. |
5 |
|
12 |
Acquires a comprehensive knowledge about methods and tools of computer engineering and their limitations. |
0 |
| * Contribution levels are between 0 (not) and 5 (maximum). |
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| Student Workload - ECTS |
| Works | Number | Time (Hour) | Total Workload (Hour) |
| Course Related Works |
|
Class Time (Exam weeks are excluded) |
16 |
3 |
48 |
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Out of Class Study (Preliminary Work, Practice) |
16 |
3 |
48 |
| Assesment Related Works |
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Homeworks, Projects, Others |
13 |
2 |
26 |
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Mid-term Exams (Written, Oral, etc.) |
0 |
0 |
0 |
|
Final Exam |
1 |
20 |
20 |
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Total Workload: | 142 |
| Total Workload / 25 (h): | 5.68 |
| ECTS Credit: | 6 |
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