COURSE UNIT TITLE

: PROBABILITY AND RANDOM SIGNAL PRINCIPLES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
EED 3005 PROBABILITY AND RANDOM SIGNAL PRINCIPLES COMPULSORY 4 0 0 5

Offered By

Electrical and Electronics Engineering

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSOCIATE PROFESSOR DAMLA GÜRKAN KUNTALP

Offered to

Electrical and Electronics Engineering

Course Objective

Purpose of the course is to introduce the fundamental concepts of random variables and random processes.

Learning Outcomes of the Course Unit

1   . To be able to model random experiments and their nondeterministic outcomes
2   To be able to apply the probability laws such as total probability, independence, conditional probability, unconditional probability, Bayes Theorem, Central Limit Theorem to engineering problems concerning random experiments
3   To be able to identify, model and analyze nondeterministic sources in enginnering problems
4   To be able to use models of known discrete and continuous random variables to define nondeterministic events in engineering problems
5   To be able to define and use tools such as probability mass function, probability density function, and probability distribution function in solving probabilistic problems in engineering
6   To be able to identify, model, classify and analyze random signals in engineering problems
7   To be able to represent random signals in frequency domain using power spectral density concept
8   To be able find the responses of linear time-invariant systems to random input signals

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Definition of random experiments, modeling of random experiments and different definitions of probability
2 Axiomatic Probability Theory, joint , conditional, unconditional probability definition, independence, Bayes theorem
3 Binomial Law, Poisson Law
4 Concept of random variables, types of random variables, Discrete random variables, probability mass, probability distribution, and probability density function, families of discrete random variables
5 Continuous random variables, probability distribution, and probability density function, families of continuous random variables
6 Expected value,moments of random variables, functions of random variables
7 Multiple random variables, joint densit, distribution, and moments
8 Functions of multiple random variables, Central Limit Theorem
9 Midterm
10 Concept of random process: definition and classification
11 Spectral representation random processes
12 Response of linear time-invariant system to a random input signal
13 Some important and frequently encountered random processes
14 Midterm
15 Some important and frequently encountered random processes

Recomended or Required Reading

Ana kaynak: Proabability & Stochastic processes, 2nd ed. by R.D. Yates, D.J.Goodman, Wiley
Yardımcı kaynaklar: Probabaility, Statistics and Random Processes for Electrical Enginneering, 3rd ed. by A.L. Garcia, Pearson
Referanslar:
Diğer ders materyalleri: Probabaility and Statistics in Engineering, 4th ed., by W.W.Hines,
D. Montgomery, D.M. Goldsman,C.M. Borror, Wiley

Planned Learning Activities and Teaching Methods

Lectures will be supported by regularly assigned homeworks and resitation hours in class. There will be unannounced quizes in some of the lectures.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE1 MIDTERM EXAM 1
2 MTE2 MIDTERM EXAM 2
3 PRC PRACTICE
4 FIN FINAL EXAM
5 FCG FINAL COURSE GRADE MTE1 * 0.25 + MTE2 * 0.25 + PRC * 0.10 + FIN * 0.40
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) MTE1 * 0.25 + MTE2 * 0.25 + PRC * 0.10 + RST * 0.40


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Learning outcomes will be tested and evaluated through weekly quizes and term exams.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

damla.kuntalp@deu.edu.tr
Ofice Ph #: 232-3017166

Office Hours

To be announced at the beginning of the semester.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 12 4 48
Preparations before/after weekly lectures 12 2 24
Preparation for midterm exam 2 6 12
Preparation for final exam 1 15 15
Preparation for quiz etc. 5 2 10
Final 1 2 2
Midterm 2 2 4
Quiz etc. 5 0,5 5
TOTAL WORKLOAD (hours) 120

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13
LO.12
LO.2443
LO.344
LO.4442
LO.555
LO.6452
LO.744
LO.8442