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Adaptive Signal Processing
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Adaptive Signal Processing
by Prof. Mrityunjoy Chakraborty

An adaptive filter is a system with a linear filter that has a transfer function controlled by variable parameters and a means to adjust those parameters according to an optimization algorithm. Because of the complexity of the optimization algorithms, almost all adaptive filters are digital filters. Adaptive filters are required for some ap...

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About This Course

An adaptive filter is a system with a linear filter that has a transfer function controlled by variable parameters and a means to adjust those parameters according to an optimization algorithm. Because of the complexity of the optimization algorithms, almost all adaptive filters are digital filters. Adaptive filters are required for some ap...

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Course Curriculum
1 Sections | 41 Lecture | 38h 21min total length
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Adaptive Signal Processing

Adaptive Signal Processing

| 38h 21min total length
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    Lecture - 1 Introduction to Adaptive Filters

    53m <?php echo $alt; ?>
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    Lecture - 2 Introduction to Stochastic Processes

    59m <?php echo $alt; ?>
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    Lecture - 3 Stochastic Processes

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    Lecture - 4 Correlation Structure

    57m <?php echo $alt; ?>
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    Lecture - 5 FIR Wiener Filter (Real)

    57m <?php echo $alt; ?>
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    Lecture - 6 Steepest Descent Technique

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    Lecture - 7 LMS Algorithm

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    Lecture - 8 Convergence Analysis

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    Lecture - 9 Convergence Analysis (Mean Square)

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    Lecture - 10 Convergence Analysis (Mean Square)

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    Lecture - 11 Misadjustment and Excess MSE

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    Lecture - 12 Misadjustment and Excess MSE

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    Lecture - 13 Sign LMS Algorithm

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    Lecture - 14 Block LMS Algorithm

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    Lecture - 15 Fast Implementation of Block LMS Algorithm

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    Lecture - 16 Fast Implementation of Block LMS Algorithm

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    Lecture - 17 Vector Space Treatment to Random Variables

    51m <?php echo $alt; ?>
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    Lecture - 18 Vector Space Treatment to Random Variables

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    Lecture - 19 Orthogonalization and Orthogonal Projection

    55m <?php echo $alt; ?>
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    Lecture - 20 Orthogonal Decomposition of Signal Subspaces

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    Lecture - 21 Introduction to Linear Prediction

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    Lecture - 22 Lattice Filter

    58m <?php echo $alt; ?>
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    Lecture - 23 Lattice Recursions

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    Lecture - 24 Lattice as Optimal Filter

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    Lecture - 25 Linear Prediction and Autoregressive Modelin

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    Lecture - 26 Gradient Adaptive Lattice

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    Lecture - 27 Gradient Adaptive Lattice

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    Lecture - 28 Introduction to Recursive Least Squares

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    Lecture - 29 RLS Approach to Adaptive Filters

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    Lecture - 30 RLS Adaptive Lattice

    1h 61 min <?php echo $alt; ?>
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    Lecture - 31 RLS Lattice Recursions

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    Lecture - 32 RLS Lattice Recursions

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    Lecture - 33 RLS Lattice Algorithm

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    Lecture - 34 RLS Using QR Decomposition

    59m <?php echo $alt; ?>
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    Lecture - 35 Givens Rotation

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    Lecture - 36 Givens Rotation and QR Decomposition

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    Lecture - 37 Systolic Implementation

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    Lecture - 38 Systolic Implementation

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    Lecture - 39 Singular Value Decomposition

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    Lecture - 40 Singular Value Decomposition

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    Lecture - 41 Singular Value Decomposition

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