1. Noise removal algorithm using Butterworth filter.
2. Signal representation in time-frequency domain using S-transform.
3. Development of LMS algorithm for parameter estimation.
4. Development of RLS algorithm for time series prediction.
5. Development of DCT based Data Compression technique.
6. R- Peak Detection of ECG signal based on Pan-Tompkins method.
7. Incremental and diffusion algorithm implementation in sensor network.
8. FIR filter design using TMS 6000 processor.
9. Noise reduction of speech signal using TMS 6000 processor.
10. Minor Project

To design and development of algorithms for signal processing application using S-transform, LMS, RLS etc.

To develop and model the real time software using application of signal processing

A student will be able to develop the algorithm for signal processing application using S-transform, LMS, RLS and to design the filter for reduction of noise of speech signal using TMS 6000 processor and to apply these techniques for real time problems.

J.G. Proakis and D.G. Manolakis, Digital Signal Processing: Principles Algorithms and Applications, Pearson Education