Seminar Topics

WAVELETS

Wavelets are advanced mathematical functions that fragment data into different frequency components based on some properties, and then study each component with a resolution matched to its scale. They have advantages over traditional Fourier methods in analyzing physical situations where the signal contains discontinuities and sharp spikes. This is because Wavelets analyze each fragment based on a different scale.

Wavelets were developed independently in the fields of mathematics, quantum physics, electrical engineering, and seismic geology. Interchanges between these fields during the last ten years have led to numerous wavelet applications such as image compression, turbulence, human vision, radar, and earthquake prediction.

The paper describe the history of wavelets beginning with Fourier, compare wavelet transforms with Fourier transforms, state properties and other special aspects of wavelets, and finish with some interesting applications such as image compression, musical tones, and de-noising noisy data.