1. Write programs for (a) linear convolution of two sequences, (b) for circular convolution, (c) performing linear convolution using circular convolution.
2. Write a program to perform (a) N-point DFT, (b) IDFT on the result obtained in (a) to verify the result, (c) circular correlation using direct method, (d) circular convolution using rotation method, (e) circular convolution and correlation using DFT
3. Learn how to use a DSP processor for finding (a) convolution of two given sequences and (b) N-point DFT in the hardware.
4. Interfacing of external device (scope) for spectrum analysis using AUDIO CODEC of the given processor for hardware implementation.
5. Compute frequency response of a hardware implemented moving average filter and show both magnitude and phase response in the scope of interfaced external device (DSO).
6. For a given input signal and a moving average filter, analyse the filtered output signal showing spectrum of it. Compute energy content of the filtered signal and compare it with actual energy content of the input signal.
7. Write a program to compute and plot the error performance surface.
8. Write a program for Adaptive filtering using LMS Algorithm.
9. Write a program for System identification and channel equalization using different LMS algorithm and compare the performance.
10. Write a program for System identification and channel equalization using different RLS algorithm.
Mini Project:
Design of IIR digital filter for filtering out female voice from a signal consists of both male and female voices together.

To learn design of digital FIR and IIR filters with real-time applications in signal conditioning.

To learn the applicability of multirate systems and their applications for signal analysis and synthesis.

To learn adaptive system designing for signal filtering and tracking applications.

d. Allow the filtered output to a DAC and finally to the speaker connected to the processor to check the functionality of the designed IIR digital filter. e. Active noise cancellation using Adaptive filtering (TMS processor).

CO1: Familiarization with the MATLAB to perform digital filter design and filtering.
CO2: To be able to design digital FIR and IIR filters as per the requirements of passband and stopband.
CO3: To be able to design a computationally efficient multirate system to interface different digital blocks operating at different sampling rates.
CO4: Learning the design of adaptive systems and their application in system identification, prediction, and interference removal.
CO5: To learn about the model basedlinear and non-linear filtering for signal processing applications.

Sanjit K. Mitra, Digital Signal Processing: A Computer-Based Approach, McGraw Hill Education , 2013, 4th Edition.