AP4112 Signal Processing Laboratory Syllabus:
AP4112 Signal Processing Laboratory Syllabus – Anna University PG Syllabus Regulation 2021
COURSE OBJECTIVES:
To provide the student with the basic understanding of audio signal analysis using filters
To provide the students with the understanding of the working of statistical method based approaches
To impart the students with the design of filters
To demonstrate the working of algorithms for different applications
To provide knowledge of analyzing the images and video
LIST OF EXPERIMENTS:
1. Design of Adaptive channel equalizer
2. Realization of sub band filter using linear convolution
3. Realization of STFT using FFT
4. Demonstration of Bayes technique
5. Demonstration of Min-max technique
6. Realization of FIR Wiener filter
7. Generation of Multivariate Gaussian generated data with desired mean vector and the required co-variance matrix.
8. Design and Realization of the adaptive filter using LMS algorithm (solved using steepestdescent algorithm)
9. Representation of the 2D image signal as the linear combinations of PCA (Eigen faces)
10. Image compression using Discrete cosine transformation (DCT).
11. Multiple-input Multiple output (MIMO)
12. Speech recognition using Support Vector Machine (SVM)
13. LMS filtering implementation using TMS320C6x processor
14. Face detection and tracking in video using OpenCV
TOTAL :45 PERIODS
COURSE OUTCOMES:
CO1: Obtain the ability to apply knowledge of linear algebra, random process and multirate signal processing in various signal processing applications.
CO2: Develop the student’s ability on conducting engineering experiments, analyze experimental observations scientifically
CO3: Become familiar to fundamental principles of linear algebra
CO4: Familiarize the basic operations of filter banks through simulations
CO5: Apply the principles of random process in practical applications
REFERENCES
1. Vinay K.Ingle,John G.Proakis, Digital signal processing using MATLAB, Cengage Learning, 3rd edition, 2011
2. Michael R King, Nipa Mody, Numerical and statistical methods for Bio Engineering – Applications using MATLAB , CAMBRIDGE University Press, 2010
3. V. Siahaan, R.H.Sianipar, Signal and Image processing with python GUI, Balige Publishing,2021