ADAPTIVE SIGNAL PROCESSING

Video Lectures Series on Adaptive Signal Processing by Prof.M.Chakraborty, Department of E and ECE, IIT Kharagpur.

Lecture - 1 Introduction to Adaptive Filters.
Lecture - 2 Introduction to Stochastic Processes.
Lecture - 3 Stochastic Processes.
Lecture - 4 Correlation Structure.
Lecture - 5 FIR Wiener Filter (Real).
Lecture - 6 Steepest Descent Technique.
Lecture - 7 LMS Algorithm

Lecture - 8 Convergence Analysis

Lecture - 9 Convergence Analysis (Mean Square) (P1)

Lecture - 10 Convergence Analysis (Mean Square) (P2)

Lecture - 11 Misadjustment and Excess MSE (P1)

Lecture - 12 Misadjustment and Excess MSE (P2)

Lecture - 13 Sign LMS Algorithm

Lecture - 14 Block LMS Algorithm

Lecture - 15 Fast Implementation of Block LMS Algorithm (P1)

Lecture - 16 Fast Implementation of Block LMS Algorithm (P2)

Lecture - 17 Vector Space Treatment to Random Variables (P1)

Lecture - 18 Vector Space Treatment to Random Variables (P2)

Lecture - 19 Orthogonalization and Orthogonal Projection

Lecture - 20 Orthogonal Decomposition of Signal Subspaces

Lecture - 21 Introduction to Linear Prediction

Lecture - 22 Lattice Filter

Lecture - 23 Lattice Recursions

Lecture - 24 Lattice as Optimal Filter

Lecture - 25 Linear Prediction and Autoregressive Modeling

Lecture - 26 Gradient Adaptive Lattice

Lecture - 27 Gradient Adaptive Lattice Contd.

Lecture - 28 Introduction to Recursive Least Squares

Lecture - 29 RLS Approach to Adaptive Filters

Lecture - 30 RLS Adaptive Lattice

Lecture - 31 RLS Lattice Recursions (P1)

Lecture - 32 RLS Lattice Recursions (P2)

Lecture - 33 RLS Lattice Algorithm

Lecture - 34 RLS Using QR Decomposition

Lecture - 35 Givens Rotation

Lecture - 36 Givens Rotation and QR Decomposition

Lecture - 37 Systolic Implementation

Lecture - 38 Systolic Implementation Contd.

Lecture - 39 Singular Value Decomposition (P1)

Lecture - 40 Singular Value Decomposition (P2)

Lecture - 41 Singular Value Decomposition (P3)

These Videos are available at the following link

CLICK HERE

Please feel free to leave a comment if there is a dead link or a problem with the links.

Read more ...

Digital Signal Processing Video Lectures

Course Description

This course was developed in 1987 by the MIT Center for Advanced Engineering Studies. It was designed as a distance-education course for engineers and scientists in the workplace.

Advances in integrated circuit technology have had a major impact on the technical areas to which digital signal processing techniques and hardware are being applied. A thorough understanding of digital signal processing fundamentals and techniques is essential for anyone whose work is concerned with signal processing applications.

Digital Signal Processing begins with a discussion of the analysis and representation of discrete-time signal systems, including discrete-time convolution, difference equations, the z-transform, and the discrete-time Fourier transform. Emphasis is placed on the similarities and distinctions between discrete-time. The course proceeds to cover digital network and non-recursive (finite impulse response) digital filters. Digital Signal Processing concludes with digital filter design and a discussion of the fast Fourier transform algorithm for computation of the discrete Fourier transform.

Instructors:

Prof. Alan V. Oppenheim

Video Lectures:

Demonstration 1: Sampling, Aliasing, and Frequency Response, Part 1. (Go to this video)

Demonstration 2: Sampling, Aliasing, and Frequency Response, Part 2. (Go to this video)

Lecture 1: Introduction. (Go to this video)

Lecture 2: Discrete-Time Signals and Systems, Part 1. (Go to this video)

Lecture 3: Discrete-Time Signals and Systems, Part 2. (Go to this video)

Lecture 4: The Discrete-Time Fourier Transform. (Go to this video)

Lecture 5: The z-Transform. (Go to this video)

Lecture 6: The Inverse z-Transform. (Go to this video)

Lecture 7: z-Transform Properties. (Go to this video)

Lecture 8: The Discrete Fourier Series. (Go to this video)

Lecture 9: The Discrete Fourier Transform. (Go to this video)

Lecture 10: Circular Convolution. (Go to this video)

Lecture 11: Representation of Linear Digital Networks. (Go to this video)

Lecture 12: Network Structures for Infinite Impulse Response (IIR) Systems. (Go to this video)

Lecture 13: Network Structures for Finite Impulse Response (FIR) Systems and Parameter Quantization Effects in Digital Filter Structures. (Go to this video)

Lecture 14: Design of IIR Digital Filters, Part 1. (Go to this video)

Lecture 15: Design of IIR Digital Filters, Part 2. (Go to this video)

Lecture 16: Digital Butterworth Filters. (Go to this video)

Lecture 17: Design of FIR Digital Filters. (Go to this video)

Lecture 18: Computation of the Discrete Fourier Transform, Part 1. (Go to this video)

Lecture 19: Computation of the Discrete Fourier Transform, Part 2. (Go to this video)

Lecture 20: Computation of the Discrete Fourier Transform, Part 3. (Go to this video)

Lecture Notes:

LEC #	TOPICS	LECTURE NOTES	PROBLEM SOLUTIONS
1	Introduction	(PDF)
2	Discrete-time signals and systems, part 1	(PDF)	(PDF)
3	Discrete-time signals and systems, part 2	(PDF)	(PDF)
4	The discrete-time Fourier transform	(PDF)	(PDF)
5	The z-transform	(PDF)	(PDF)
6	The inverse z-transform	(PDF)	(PDF)
7	Z-transform properties	(PDF)	(PDF)
8	The discrete Fourier series	(PDF)	(PDF)
9	The discrete Fourier transform	(PDF)	(PDF)
10	Circular convolution	(PDF)	(PDF)
11	Representation of linear digital networks	(PDF)	(PDF)
12	Network structures for infinite impulse response (IIR) systems	(PDF)	(PDF)
13	Network structures for finite impulse response (FIR) systems and parameter quantization effects in digital filter structures	(PDF)	(PDF)
14	Design of IIR digital filters, part 1	(PDF)	(PDF)
15	Design of IIR digital filters, part 2	(PDF)	(PDF)
16	Digital Butterworth filters	(PDF)	(PDF)
17	Design of FIR digital filters	(PDF)	(PDF)
18	Computation of the discrete Fourier transform, part 1	(PDF)	(PDF)
19	Computation of the discrete Fourier transform, part 2	(PDF)	(PDF)
20	Computation of the discrete Fourier transform, part 3	(PDF)	(PDF)

For more information you can visit the following link:

Click Here

Please feel free to leave a comment if there is a dead link or a problem with the links.

Read more ...

Wavlet Tutorials

Wavlet means a little or a small wave localized in a certain time. These wavlets are used in transformation of a signal from time domain to time-scale (frequency) representation of a signal. Wavlet transform is a tool used to analyze raw signals and have many applications in DSP.

Here are links to lectures introducing wavlet transform from the university of St. Thomas :

Lecture Slides - 2011

Lecture 1 - Why Wavelets? PDF File
Lecture 2 - Digital Image Basics PDF File
Lecture 3 - The Discrete Haar Wavelet Transform PDF File
Lecture 4 - Coding the Haar Wavelet Transform PDF File
Lecture 5 - Measurements PDF File
Lecture 6 - Huffman Coding PDF File
Lecture 7 - The HWT and Image Compression PDF File
Lecture 8 - Daubechies Filters PDF File
Lecture 9 - Fourier Series and Filter Design PDF File
Lecture 10 - Biorthogonal Filters PDF File

An Introduction to Wavelets and Their Application to Digital Imaging -2009

Lecture 1 - Why Wavelets? PDF File

Lecture 2 - Huffman Codes PDF File

Lecture 3 - Discrete Haar Wavelet Transforms PDF File

Handout Problems - The Haar Wavelet Transform PDF File

Lecture 4 - Digital Image Compression PDF File

Lecture Slides - 2009

Lecture 1 - Why Wavelets? PDF File

Lecture 2 - Digital Image Basics PDF File

Lecture 3 - The Discrete Haar Wavelet Transform PDF File

Lecture 4 - Coding the Haar Wavelet Transform PDF File

Lecture 5 - Measurements PDF File

Lecture 6 - Huffman Coding PDF File

Lecture 7 - The HWT and Image Compression PDF File

Lecture 8 - Daubechies Filters PDF File

Lecture 9 - Fourier Series and Filter Design PDF File

Lecture 10 - Biorthogonal Filters PDF File

Lecture 11 - Classical Theory and Daubechies Wavelets PDF File

Lecture 12 - FBI Fingerprint Compression PDF File

Student Project - FBI Fingerprint Compression 2003 ppt File

Student Project - FBI Fingerprint Compression 2007 ppsx File

Lecture Slides - 2008

Lecture 1 - Why Wavelets? PDF File

Lecture 2 - Images, Measures, and Huffman Codes PDF File

Lecture 3 - Fourier Series, Convolution, and Filters PDF File

Lecture 4 - The Haar Wavelet Transform PDF File

Lecture 5 - Applications of the HWT PDF File

Lecture 6 - Daubechies Filters PDF File

Lecture 7 - Classical Theory PDF File

Lecture 8 - Biorthogonal Filters PDF File

Lecture 8.5 - Denoising PDF File

Lecture 9 - The Lifting Method PDF File

Lecture 10 - JPEG2000 PDF File

Lecture Slides - 2007

Lecture 1 - Why Wavelets? PDF File

Lecture 2 - Images, Measures, and Huffman Codes PDF File

Lecture 3 - Fourier Series, Convolution, and Filters PDF File

Lecture 4 - The Haar Wavelet Transform PDF File

Lecture 5 - Applications of the HWT PDF File

Lecture 6 - Daubechines Filters PDF File

Lecture 7 - Denoising PDF File

Lecture 8 - Biorthogonal Filters PDF File

Lecture 9 - The Lifting Method PDF File

Lecture 10 - JPEG2000 PDF File

Lecture Slides - 2006

Lecture 1 - Why Wavelets? PDF File

Lecture 2 - Images, Measures, and Huffman Codes PDF File

Lecture 3 - Fourier Series, Convolution, and Filters PDF File

Lecture 4 - Discrete Haar Wavelet Transforms PDF File

Lecture 5 - Applications: Compression and Edge Detection PDF File

Lecture 6 - Daubechies Filters PDF File

Lecture 7 - Application: Signal Denoising PDF File

Lecture 10 - JPEG2000 Image Compression Standard PowerPoint File

For more information you can visit the following link :

Wavlet Home

Also there is a good tutorial about Wavlet Transform (see the following links):

Wavlet Tutorial - Part1 (OVERVIEW: WHY WAVELET TRANSFORM?)

Wavlet Tutorial - Part2 (FUNDAMENTALS: THE FOURIER TRANSFORM AND THE SHORT

                                   TERM FOURIER TRANSFORM, RESOLUTION PROBLEMS) 

Wavlet Tutorial - Part3 (MULTIRESOLUTION ANALYSIS:THE CONTINUOUS WAVELET

                                   TRANSFORM)

Wavlet Tutorial - Part4 (MULTIRESOLUTION ANALYSIS:THE DISCRETE WAVELET

                                    TRANSFORM)

Please feel free to leave a comment if there is a dead link or a problem with the links.

Read more ...