Faculty-In-Charge

Dr. Anup Aprem, Assistant Professor, ECED

Staff-In-Charge

Ms. Anjali M R, Technician, ECED

Location and Room No

ECED Block-II, 201

Course

Semester

EC6402E: Advanced Digital Signal Processing

Monsoon 

EC6403E: Probability Theory and Applications

Monsoon 

EC6411E: Machine Learning Lab 

Monsoon 

EC6405E:  Statistical Signal Processing

Winter 

EC6448E: Foundations of Data Analytics 

Winter 

EC6423E: Digital Image Processing Techniques

Winter

EC6496E: Project Phase I

Monsoon

EC7496E: Project Phase II

Summer

EC7498E: Project Phase III

Monsoon

EC7499E: Project Phase IV

Winter

Sl. No

Equipments

1

Desktop Computers

2

Workstations (with GPU)

Sl. No

Name

1.

MATLAB 

2.

Anaconda Data Analysis Stack using Python

3. 

Deep Learning Software Stack: PyTorch, TensorFlow, Keras, Cuda

List of Experiments

1

Analysis and interpretation of DFT Spectrum using simple and practical signals.

2

Convolution of two sequences- Convolution applied to audio/voice signals.

3

IIR filter design and applications – Suppression of power supply hums in audio signals, artificial reverberations, Generation and detection of DTMF tones.

4

FIR filter design and applications- Filtering effects on voice signals, Filtering of Sinusoidal Noise interference. 

5

Implement filter structures and study the effects of quantization and overflow errors. 

6

Study the effect of decimation and interpolation operations using standard signals.

7

Design and implement a 2-Channel uniform DFT filter bank using linear phase FIR filters. 

8

Study the effect of sampling rate and quantization on the sound quality of audio signals. 

9

Application of 2D convolution and 2D transforms. 

10

Study the effect of different noise models: Gaussian, Impulse (salt and pepper) and Poisson noise on images.  Also study the effect of Mean, Median, and Mode filters on signal-to-noise ratio of  the noisy images. 

11

Course Project 

List of Experiments

1

Generation of continuous and discrete random variables

2

Empirical computation of distribution of conditional random variables

3

Generation of vector random variables.

4

Application of law of large numbers to Monte Carlo integration.

5

Simulation of Discrete time Markov chain

6

Estimation of power spectral density using white noise.

7

AEP and Shannon source coding theorem

List of Experiments

1

Simulating central limit theorem, estimation of probability density function using parametric and nonparametric methods

2

Classification using Bayes discriminant function

3

Dimensionality reduction using FLD and PCA

4

Simulation of an X-OR problem and its classification using an MLP.

5

Implementation of the back-propagation algorithm. Classification of a 4 dimensional 3-class problem using FLD and MLP

6

Introduction to modern machine learning libraries such as scikit-learn, Tensorflow, and Pytorch

7

Implementation of an ROC and result analysis from ROC.

8

Implementation of Viterbi algorithm

9

End semester mini project.

List of Experiments

1

Maximum likelihood modelling for various applications. 

2

Empirical computation of estimator variance and comparison with CRLB

3

Sinusoidal frequency estimation

4

Least square modelling

5

AR and MA modelling for various practical applications

6

AR parameter estimation using Levinson-Durbin algorithm

7

FIR Weiner filtering

8

Innovations Algorithm

9

Binary hypothesis testing under various decision frameworks

List of Experiments

1

Python Programming Basics

2

Normalizing a database to normal form

3

Creating, Querying and searching in SQL

4

Parsing XML in Python

5

Pandas: Data cleaning and wrangling

6

Matplotlib: Basic data visualization

7

Advanced data visualization 

List of Experiments

1

Image Denoising and Restoration

2

Image Enhancement for Low-light Images

3

Edge Detection Using Morphological Operations

4

Segmentation of Medical Images

5

Image Inpainting/Content-aware Filling

6

Image Super-resolution Using Deep Learning

7

Implementation of Advanced 2D filters: