Digital Signal Processing Lab
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Digital Signal Processing Lab - SENSE
Overview
The Digital Signal Processing (DSP) Lab is a core teaching facility under the School of Electronics Engineering (SENSE), Vellore Institute of Technology, Vellore, established to provide a strong foundation in signal analysis and processing techniques. The lab primarily supports undergraduate (UG) B.Tech students for the course Digital Signal Processing, enabling them to understand both theoretical and practical aspects of DSP concepts. The lab is equipped with more than 50 computers installed with the latest MATLAB licensed software, allowing students to perform advanced simulations and algorithm development. Additionally, it features TMS320C6748 processor kits for real-time hardware implementation of DSP applications, bridging the gap between simulation and embedded deployment. The facility also encompasses GPU-enabled systems to support high-performance simulation and Al-based signal processing projects, thereby equipping students with skills relevant to modern industry and research requirements.
Objectives
- To provide practical exposure to the usage of appropriate software and hardware tools for realizing signal processing modules through structured laboratory experiments.
- To strengthen students' skills in designing and implementing signal processing systems based on fundamental DSP concepts.
- To support course-integrated experiments, mini-projects, and real-time DSP application development.
- To promote good engineering practices, including analysis, validation, and optimization of signal processing systems.
Key Focus Areas
- TMS320C6748 architecture, Code Composer Studio {CCS) IDE, program development, and debugging techniques.
- Generation of elementary signals and implementation of basic signal processing operations on DSP hardware.
- Sampling and reconstruction of continuous-time signals, along with OFT-based spectral analysis.
- Processing and analysis of biomedical, speech, and audio signals using DSP techniques.
- Efficient computational analysis using Fast Fourier Transform (FFT) algorithms.
- Design and implementation of IIR and FIR Filters
