Adaptive Signal Processing

Indian Institute of Technology Kharagpur

This course covers lessons on Adaptive Filters,Stochastic Processes ,Correlation Structure,Convergence Analysis,LMS Algorithm,Vector Space Treatment to Random Variables,Gradient Adaptive Lattice, Recursive Least Squares,Systolic Implementation & Singular Value Decomposition.

Course topics:

  • Introduction to Adaptive Filters
  • Introduction to Stochastic Processes
  • Stochastic Processes
  • Correlation Structure
  • FIR Wiener Filter (Real)
  • Steepest Descent Technique
  • LMS Algorithm
  • Convergence Analysis
  • Convergence Analysis (Mean Square)
  • Misadjustment and Excess MSE
  • Sign LMS Algorithm
  • Block LMS Algorithm
  • Fast Implementation of Block LMS Algorithm
  • Vector Space Treatment to Random Variables
  • Orthogonalization and Orthogonal Projection
  • Orthogonal Decomposition of Signal Subspaces
  • Introduction to Linear Prediction
  • Lattice Filter
  • Lattice Recursions
  • Lattice as Optimal Filter
  • Linear Prediction and Autoregressive Modeling
  • Gradient Adaptive Lattice
  • Introduction to Recursive Least Squares
  • RLS Approach to Adaptive Filters
  • RLS Adaptive Lattice
  • RLS Lattice Recursions
  • RLS Lattice Algorithm
  • RLS Using QR Decomposition
  • Givens Rotation
  • Givens Rotation and QR Decomposition
  • Systolic Implementation
  • Singular Value Decomposition
Course Lectures