Course Code: EET305
Course Name: Signals and Systems
Course Objectives:
This course introduces the concept of signals and systems. The time domain and frequency domain representation, operations and analysis of both the continuous time and discrete time systems are discussed. The application of Fourier analysis, Laplace Transform and Z- Transforms are included. Stability analysis of continuous time systems and discrete time systems are also introduced.
Course Outcomes:
After the completion of the course the student will be able to:
CO 1 Explain the basic operations on signals and systems.
CO 2 Apply Fourier Series and Fourier Transform concepts for continuous time signals.
CO 3 Analyse the continuous time systems with Laplace Transform.
CO 4 Analyse the discrete time system using Z Transform.
CO 5 Apply Fourier Series and Fourier Transform concepts for Discrete time domain.
CO 6 Describe the concept of stability of continuous time systems and sampled data systems.
Curriculum
- 5 Sections
- 28 Lessons
- 10 Weeks
- MODULE 1Introduction to Signals and Systems (9 hours): Classification of signals: Elementary signals- Basic operations on continuous time and discrete time signals Concept of system: Classification of systems- Properties of systems- Time invariance- Linearity -Causality – Memory- Stability-Convolution Integral- Impulse response Representation of LTI systems: Differential equation representations of LTI systems Basics of Non linear systems- types and properties Introduction to random signals and processes (concepts only)6
- MODULE 2Fourier Analysis and Laplace Transform Analysis (10 hours): Fourier analysis of continuous time signals: Fourier Series- Harmonic analysis of common signals Fourier transform: Existence- Properties of Continuous time Fourier transform- Energy spectral density and power spectral density Concept of Frequency response Laplace transform analysis of system transfer function: Relation between the transfer function and differential equation- Transfer function of LTI systems- Electrical, translational and rotational mechanical systems- Force voltage, Force current and Torque Voltage analogy6
- MODULE 3System Models and Response (8 hours): Block diagram representation - block diagram reduction Signal flow graph - Mason's gain formula Type and Order of the systems- Characteristic equation Determining the time domain and frequency response from poles and zeros Concepts of Positive real functions and Hurwitz polynomial- Routh stability criterion. Simulation based analysis: Introduction to simulation tools like MATLAB/ SCILAB or equivalent for mathematical and signal operations (Demo/Assignment only)5
- MODULE 4Sampled Data Systems and Z-Transform (9 hours): Sampling process-Impulse train sampling-sampling theorem- Aliasing effect Zero order and First order hold circuits- Signal reconstruction Discrete convolution and its properties Z Transform: Region of convergence- Properties of Z Transform Inverse ZT: Methods5
- MODULE 5Analysis of Sampled Data Systems (9 hours): Difference equation representations of LTI systems - Analysis of difference equation of LTI systems- Z Transfer function- Delay operator and block diagram representation- Direct form, cascade and parallel representations of 2nd order systems Stability of sampled data system: Basic idea on stability- Jury's test- Use of bilinear transformation Discrete Fourier series: Fourier representation of discrete time signals - Discrete Fourier series– properties. Discrete Time Fourier Transform: Properties- Frequency response of simple DT systems6
