Wavelets play an essential role in modern signal processing and appear in many applications in electromagnetism, scattering, image analysis and acoustics.
In this course it will be described how to use the short-time Fourier transform to gain information about both the time domain and frequency domain, use the continuous wavelet transform to analyze signals with both slow and fast rate of change, and several different methods and concepts for analyzing and recreating signals such as multiresolution analysis, Daubechies orthonormal wavelet bases and more.
Course study guide
Recommended course materials, online resourses and literature
Introduction to Transform Theory with Applications.
This is an excellent introductory repetition material reviewing in concrete and practical way standard transforms such as Laplace transform (LP), Fourier transform (FT), discrete FT, wavelet transform and more.
Basics of Wavelets tutorial by
Wavelets, Filter Banks and Applications
Gilbert Strang, and Kevin Amaratunga. (MIT course number 18.327)
Wavelets, Filter Banks and Applications, Spring 2003.
Massachusetts Institute of Technology: MIT OpenCourseWare http://ocw.mit.eduhttp://ocw.mit.eduhttp://ocw.mit.eduhttp://ocw.mit.eduhttp://ocw.mit.eduhttp://ocw.mit.eduhttp://ocw.mit.eduhttp://ocw.mit.eduhttp://ocw.mit.edu
Wavelets toure of Signal processing
Links to websites for this excellent book several editions with usefull suplementary resources, numerical wavelets software and links:
Other recommended resources and literature on Wavelets
Wavelets, Spring 2014.
PhD (post-graduate) education level course Wavelets was given for the first time at Mälardalen University byin Spring 2014
Lecture notes/slides of the lectures by Anatoliy Malyarenko:
Book by Professor Palle Jorgensen from University of Iowa, USA
Graduate Texts in Mathematics, Vol. 234, Springer
Usefull online resourses on Wavelets:
Youtube open access lectures on Wavelets:
Professor Ole Christensen, DTU (Technical University of Denmark)
(Note: Part 1 of this lecture is mostly about Fourier Transform and convolution properties only with no wavelets involved. Thus, one can start from Part 2 directly concerned with Wavelets.)
Examiner: Professor Sergei Silvestrov