Course Details
Subject {L-T-P / C} : EC6675 : Signal Processing Application Laboratory { 0-0-3 / 2}
Subject Nature : Practical
Coordinator : Lakshi Prosad Roy
Syllabus
| Module 1 : |
Introduction to basics of computer based signal generation, real-time data acquisition and their processing using MATLAB and Python. |
| Module 2 : |
Computer based statistical signal generation, analysis and processing using MATLAB.: (a) Computer generation of variety noises, (b) Variety fundamental waveforms corrupted by such noises, (c) Moving average filtering of the noise corrupted waveforms. |
| Module 3 : |
Design and implementation of a Butterworth filter and FIR filter for noise removal. |
| Module 4 : |
Design and implementation of Real-time ultrasonic sensor based distance measurement system applying Least Mean Square (LMS) algorithm for signal estimation. |
| Module 5 : |
a) Measurement of time period (and then frequency of oscillation) of moving pendulum with various lengths of string using a motion sensor.
|
| Module 6 : |
a) Measurement of various rotations per minute (RPM) of a moving fan with multiple blades by motion sensor and signal processing tools of MATLAB and Python.
|
| Module 7 : |
Design and implementation of Real-time Motion sensor based velocity measurement system using Python codes in Raspberry-Pi. |
| Module 8 : |
NVIDIA Jetson processor based real-time RGB image processing. |
| Module 9 : |
NVIDIA Jetson processor based biomedical signal and image processing. |
| Module 10 : |
Mini Project. |
Course Objective
| 1 . |
To learn computer based signal generation, simulation of practical data (patterns that closely match real-world information) and processing of signal for information retrieval. |
| 2 . |
Real-time data acquisition and signal processing using MATLAB and Python programming languages. |
| 3 . |
Design and implementation of signal processing systems using Raspberry-Pi and NVIDIA Jetson processor for real-time signal and image processing. |
Course Outcome
| 1 . |
Students will able to simulate practical data (patterns that closely match real-world information) and process the same for information retrieval in various applications. |
| 2 . |
Students will able to implement specialized filtering algorithms for noise or interference removal from signals of variety applications. |
| 3 . |
Students will able to design and implement real-time data acquisition systems and processing in various compter programming languages. |
| 4 . |
Students will get hands-on experience in implementing the signal processing systems utilizing Raspberry-Pi, NVIDIA Jetson processor and also desktop/laptop. |
Essential Reading
| 1 . |
J.G. Proakis and D.G. Manolakis, Digital Signal Processing: Principles Algorithms and Applications, Pearson Education |
Supplementary Reading
| 1 . |
S.M.Kay, Fundamentals of Statistical Signal Processing: Estimation Theory, Pearson, 2010 |
Journal and Conferences
| 1 . |