COURSE SUMMARY
Course Title: 
Adaptive Signal Processing
Course Code: 
15ECE321
Year Taught: 
2015
Type: 
Elective
Degree: 
Undergraduate (UG)
School: 
School of Engineering
Campus: 
Bengaluru
Chennai
Coimbatore
Amritapuri

'Adaptive Signal Processing' is an elective course offered for the B. Tech. (Bachelor of Technology) in Electronics and Communication Engineering at School of Engineering, Amrita Vishwa Vidyapeetham.

Unit 1

Adaptive Systems - Definition and characteristics – Properties - Applications and examples of an adaptive system. Stochastic Processes and Models: Characterization - Mean ergodic theorem - Correlation matrix - Stochastic models - Power spectral density - Properties of power spectral Density - Linear transformations - Power spectral estimation.

Unit 2

Wiener filters - Linear optimum filtering - Minimum mean-square error - Wiener- Hopf equations - Multiple linear regression model - Steepest-descent algorithm - Linear prediction - Forward linear prediction, Levinson-Durbin algorithm. Kalman filter - Extended kalman filter

Unit 3

Least-Mean-Square (LMS) adaptive filters - LMS algorithm, LMS adaptation algorithm - applications. Method of Least Squares - Data windowing, Normal equations and linear least square filters, Recursive least squares algorithm.

TEXTBOOKS

  1. Simon Haykins, “Adaptive Filter Theory”, Pearson Education, Fifth Edition, 2013.

REFERENCES

  1. Todd K. Moon, Wynn C. Stirling, “Mathematical Methods and Algorithms for Signal Processing” Prentice Hall, First edition, 1999.
  2. John. R. Triechler, C. Richard Johnson (Jr), Michael. G. Larimore, “Theory and Design of Adaptive Filters”, Prentice Hall India Private Limited, 2004
  3. Bernard Widrow and Samuel. D. Stearns, “Adaptive Signal Processing”, Pearson Education, 2001.