EEE306 SIGNALS AND SYSTEMS II
| Course Code: | 3560306 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 5.0 |
| Department: | Electrical and Electronics Engineering |
| Language of Instruction: | English |
| Level of Study: | Undergraduate |
| Course Coordinator: | Assoc.Prof.Dr. TAYFUN NESİMOĞLU |
| Offered Semester: | Spring Semesters. |
Course Objectives
To be able to:
(1) Analyze the statistical properties (probability density function (pdf), cumulative distribution function, mean, variance, moments, correlation, covariance, correlation coefficient) of multiple random variables. Identify the concepts of independence, uncorrelatedness, orthogonality of random variables. Identify Gaussian random variables and Central Limit Theorem.
(2) Identify the concept of random process. Compute and interpret the statistical parameters (mean, variance, autocorrelation, autocovariance, crosscorrelation, crosscovariance, correlation coefficient) of random processes.
(3) Identify the concepts of stationarity (strict sense stationarity, wide sense stationarity (WSS)) and ergodicity.
(4) Identify and formulate the power spectral density function for WSS random processes.
(5) Analyze the linear time invariant (LTI) systems with random inputs. Formulate the autocorrelation function and power spectral density function of output in terms of those of input.
(6) Identify Gaussian and Poisson Processes, Poisson Impulses.
(7) Identify white, thermal, shot noise.
(8) Analyze bandpass deterministic signals and modulation techniques. Apply Hilbert transform to bandpass signals.
(9) Apply the principles of deterministic bandpass signals to bandpass noise signals.
Course Content
Correlation of signals. Energy and power spectral densities. Hilbert transform. Principles of modulation. Stochastic processes: Characterization, correlation functions, stationarity, ergodicity, power spectral density. Transmission of random signals through linear systems. Special stochastic processes. Noise.
Course Learning Outcomes
Having successfully completed this course, the student will be able to to formulate, analyze, and interpret:
(1) the statistical properties of multiple random variables.
(2) the concepts of independence, uncorrelatedness, orthogonality of random variables.
(3) Gaussian random variables and Central Limit Theorem
(4) the concept of random process and the statistical parameters of random processes.
(5) the concepts of stationarity and ergodicity. [Homework, quiz, and exam]
(6) the power spectral density function for WSS random processes. [Homework, quiz, and exam]
(7) the linear time invariant systems with random inputs.
(8) the autocorrelation function and power spectral density function of output in terms of those of input.
(9) Gaussian and Poisson Processes, Poisson Impulses. [Homework, quiz, and exam]
(10) white, thermal, and shot noise. [Homework, quiz, and exam]
(11) bandpass deterministic signals and modulation techniques.
(12) Hilbert transform to bandpass signals. [Homework, quiz, and exam]
(13) the principles of deterministic bandpass signals to bandpass noise signals. [Homework, quiz, and exam]