Subject Code & Name: EC25C04 – Signals and Systems
Regulation: R-2025
Semester: III (Third Semester)
Branch: B.E. Computer and Communication Engineering (CCE)
Credits / L-T-P: 4 Credits | L-T-P: 3-1-0
Course Objectives
- The course builds foundational skills for analyzing continuous and discrete-time signals, including their classification and properties, and explores key transforms (Fourier, Laplace, Z, DTFT).
Full Unit-wise Syllabus
Unit I – Introduction to Signals and Systems
Definition of Signals and Systems, Classification of Signals, Operations on signals, Singularity functions and related functions. Analogy between vectors and signals, orthogonal signal space, complete set of orthogonal functions, Parseval's relations.
Unit II – Fourier Series Analysis
Fourier series representation of continuous time periodic signals, Trigonometric and Exponential Fourier series, Properties of Fourier series.
Unit III – Fourier Transform & Laplace Transform
Fourier transform of aperiodic signals, standard signals and periodic signals, Properties of Fourier transforms. Hilbert transform and its properties. Laplace transforms, RoC, properties. Inverse Laplace transform.
Unit IV – Continuous-Time LTI Systems
Continuous time Systems and its properties. Linear time invariant (LTI) system, Impulse response. Convolution. Analysis of LTI System using Laplace and Fourier transforms.
Unit V – Sampling, Quantization & Discrete-Time Systems
Sampling and reconstruction of band limited signals. Low pass and band pass sampling theorems. Aliasing. Anti-aliasing filter. Practical Sampling-aperture effect. Quantization. Discrete-time signals and systems. Discrete Fourier series, DTFT, Z-transform and its properties. Analysis of LTI systems using Z – transform.
Suggested Activities: Quiz based on competitive examination problems (GATE, IES), Simulation Assignment.
Course Outcomes (COs)
- CO1: Define and classify continuous-time and discrete-time signals, systems, and their fundamental properties.
- CO2: Apply Fourier Series techniques to analyze periodic signals and interpret their frequency domain characteristics.
- CO3: Analyze Linear Time-Invariant (LTI) systems using convolution and transform methods.
- CO4: Develop and adapt solutions using sampling, quantization, and discrete-time signal processing techniques for real-world applications and continuous learning.
Assessment Pattern (Quick Note)
- Weightage: Continuous Assessment 40% | End Semester Examinations 60%
- Internal methodology: Assignment (20%), Software activity (20%), Quiz (20%), Internal Examinations (40%)
Source: Official Anna University – B.E. Computer and Communication Engineering R-2025 Syllabus
Last Updated: September 2026
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