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Signals and Systems

Signals and Systems is the "logical" study of how information is represented, transmitted, and transformed. It utilizes "circuit-based technical materials" to analyze the interaction between mathematical signals and the physical systems that process them.

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Signals and Systems

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Course Title: Signals and Systems

Course No: ENEX 255

Nature of the Course: Theory + Lab

Semester: 4

Full Marks: 40 + 60 + 25

Pass Marks: 16 + 24 + 10

Credit Hours: 3

Course Description

Course Objectives

Course Contents

1. Signal and its Types

7 hrs10 marks

1.1. Introduction to signal and signal processing

1.2. Classification of signal based on dimension

1.3. Classification of one-dimensional signal (CT and DT) and properties

1.4. Fundamental signals: Delta function, unit step, ramp, rectangular pulse, signum function

1.5. Relationship between unit step and delta function

1.6. Signal classification based on causality

1.7. Classification of signals based on periodicity (CT and DT)

1.8. Transformation of the independent variable

1.9. Energy and power signals

1.10. Even and odd signals

1.11. System, types of systems: Linear and non-linear, causal and non-causal, time-invariant and time-variant

2. Fourier Series

9 hrs12 marks

2.1. Introduction to Fourier series

2.2. Fourier series representation of continuous time periodic signal

2.3. Properties of continuous time Fourier series: Linearity, time shifting, time scaling, time reversal, convolution, multiplication, frequency shifting, conjugate symmetry, Parseval's relation

2.4. Fourier series representation of discrete time periodic signal

2.5. Properties of discrete time Fourier series: Linearity, time shifting, time scaling, time reversal, convolution, modulation, conjugate symmetry, Parseval's relation

2.6. Applications of Fourier series

3. Fourier Transform

9 hrs12 marks

3.1. Introduction to Fourier transform

3.2. Continuous time Fourier transform

3.3. Properties of continuous time Fourier transform: Linearity, time shifting, frequency shifting, time scaling, time reversal, convolution, multiplication, duality, conjugation, Parseval's relation

3.4. Discrete time Fourier transform

3.5. Properties of discrete time Fourier transform: Linearity, time shifting, frequency shifting, time reversal, convolution, modulation, conjugation, Parseval's relation

3.6. Fourier transform for periodic signals

3.7. Applications of Fourier transform

4. Linear Time Invariant (LTI) System

7 hrs10 marks

4.1. Linear time invariant (LTI) system

4.2. Convolution integral properties of LTI system

4.3. Representation of discrete-time signals in terms of impulses

4.4. Convolution sum

4.5. Representation of continuous-time signals in terms of impulses

4.6. Convolution integral

4.7. Practical applications of convolution

6 hrs7 marks

5.1. Introduction to sampling

5.2. Sampling theorem

5.3. Practical consideration of sampling and impulse-train sampling

5.4. Signal reconstruction from sampled version

5.6. Band limited signals

6. Frequency Response of Continuous and Discrete Time Systems

7 hrs9 marks

6.1. Frequency response of continuous time systems

6.2. Transfer function of continuous time system

6.3. Impulse response of ideal low-pass, band-pass and high-pass filter

6.4. Response of ideal low pass filter to a step function input

6.5. Frequency and Impulse response of RC filter

6.6. Frequency response of discrete time systems: Transfer function

6.7. Impulse response of low-pass, band-pass and high-pass filter

Laboratory Works

1.Generation of continuous and discrete time signal, unit step signal, ramp signal, sinc function, sinusoidal signal, unit impulse signal, exponential signals, complex exponentials
2.Convolution: Square Wave with Odd Symmetry
3.Magnitude and Phase of Rational Signal
4.Fourier Series
5.Fourier Transform

Reference Books

1.Oppenheim, A.V., Willsky, A.S., Nawab, S.H. (2013). Signals and Systems. Pearson education second edition.
2.Oppenheim, A., Schafer, R. W. (2013). Discrete-Time Signal Processing: Pearson New International Edition. United Kingdom: Pearson Education.
3.Ingle, V. K., Proakis, J. G. (2000). Digital signal processing using MATLAB. United Kingdom: Brooks/Cole.
4.Lathi, B. P. (2010). Linear Systems and Signals. United Kingdom: Oxford University Press.

Notes:

Source:

Signals and Systems provides fundamental understanding of how signals are represented, analyzed, and processed in various systems. Topics include signal classification, Fourier series, Fourier transform, linear time invariant systems, sampling, and frequency response of continuous and discrete time systems.

The objective of this course is to provide students with a fundamental understanding of how signals are represented, analyzed, and processed in various systems. Students will grasp essential concepts such as signal classification, time and frequency domain analysis, convolution and Fourier analysis. By the end of the course, students should be proficient in solving problems related to signal processing and system analysis, enabling them to design and optimize systems effectively.

Practical sessions of 22.5 hours covering generation of continuous and discrete time signals, convolution, magnitude and phase of rational signals, Fourier series, and Fourier transform.

This syllabus follows the official BEI curriculum of Tribhuwan University. In case of any doubt or revision, the university's published syllabus shall be considered authoritative. https://ioe.tu.edu.np/pages/electronics-engineering-curriculum-structure-2660

The questions will cover all the chapters in the syllabus. There may be minor deviation in marks distribution.