Electronics - Adaptive Signal Processing (English)

   Tuesday, February 11, 2025   

Starting a new Lecture Notes Series on Electronics - Adaptive Signal Processing

Youtube Lecture Playlist Credits 

Channel Name: nptelhrd

So Let Us Start to This Journey of Learning 

Electronics - Adaptive Signal Processing By Lecture Notes together!

Lecture 1: Lecture - 1 Introduction to Adaptive Filters

Lecture 2: Lecture - 2 Introduction to Stochastic Processes

Lecture 3: Lecture - 3 Stochastic Processes

Lecture 4: Lecture - 4 Correlation Structure

Lecture 5: Lecture - 5 FIR Wiener Filter (Real)

Lecture 6: Lecture - 6 Steepest Descent Technique

Lecture 7: Lecture - 7 LMS Algorithm

Lecture 8: Lecture - 8 Convergence Analysis

Lecture 9: Lecture - 9 Convergence Analysis (Mean Square)

Lecture 10: Lecture - 10 Convergence Analysis (Mean Square)

Lecture 11: Lecture - 11 Misadjustment and Excess MSE

Lecture 12: Lecture - 12 Misadjustment and Excess MSE

Lecture 13: Lecture - 13 Sign LMS Algorithm

Lecture 14: Lecture - 14 Block LMS Algorithm

Lecture 15: Lecture - 15 Fast Implementation of Block LMS Algorithm

Lecture 16: Lecture - 16 Fast Implementation of Block LMS Algorithm

Lecture 17: Lecture - 17 Vector Space Treatment to Random Variables

Lecture 18: Lecture - 18 Vector Space Treatment to Random Variables

Lecture 19: Lecture - 19 Orthogonalization and Orthogonal Projection

Lecture 20: Lecture - 20 Orthogonal Decomposition of Signal Subspaces

Lecture 21: Lecture - 21 Introduction to Linear Prediction

Lecture 22: Lecture - 22 Lattice Filter

Lecture 23: Lecture - 23 Lattice Recursions

Lecture 24: Lecture - 24 Lattice as Optimal Filter

Lecture 25: Lecture - 25 Linear Prediction and Autoregressive Modeling

Lecture 26: Lecture - 26 Gradient Adaptive Lattice

Lecture 27: Lecture - 27 Gradient Adaptive Lattice

Lecture 28: Lecture - 28 Introduction to Recursive Least Squares

Lecture 29: Lecture - 29 RLS Approach to Adaptive Filters

Lecture 30: Lecture - 30 RLS Adaptive Lattice

Lecture 31: Lecture - 31 RLS Lattice Recursions

Lecture 32: Lecture - 32 RLS Lattice Recursions

Lecture 33: Lecture - 33 RLS Lattice Algorithm

Lecture 34: Lecture - 34 RLS Using QR Decomposition

Lecture 35: Lecture - 35 Givens Rotation

Lecture 36: Lecture - 36 Givens Rotation and QR Decomposition

Lecture 37: Lecture - 37 Systolic Implementation

Lecture 38: Lecture - 38 Systolic Implementation

Lecture 39: Lecture - 39 Singular Value Decomposition

Lecture 40: Lecture - 40 Singular Value Decomposition

Lecture 41: Lecture - 41 Singular Value Decomposition