Concepts, methodologies and tools of signal processing using wavelets, including multi-resolution analysis, wavelet packets, wavelet dictionaries, wavelet denoising and selected applications.
In this course we will focus on the concepts, methodologies and tools of signal processing using wavelets. We will discuss the basics of wavelets, and aim at the appropriate balance of theory and applications. Topics of interest include multi- resolution analysis, wavelet packets, and selected applications to data compression, denoising, and signal and image processing. The course has no specific prerequisites, although a basic knowledge of digital signal processing (e.g. Fourier transforms) transforms is recommended
The course will consist of lectures and student presentations. Students will explore the basics of wavelet and gain the hands-on experience with MATLAB® Wavelet Toolbox by doing homework assignments and a project on a topic related to the student's area of interest.
Strang, and Nguyen. Wavelets and Filter Banks. Wellesley-Cambridge Press, 1997.