Abstract—Wavelets are mathematical functions that cut up data into different frequency components, 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. Wavelets were developed independently in the ends of mathematics, quantum physics, electrical engineering, and seismic geology. Interchanges between these fields during the last ten years have led to many new wavelet applications such as image compression, turbulence, human vision, radar, and earthquake prediction. This paper introduces wavelets to the interested technical person outside of the digital signal processing field. I 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 applications.

Index Terms—Wavelet, Continuous Wavelet Transformation (CWT), Discrete Wavelet Transformation (DWT)

Cite: Dolley Shukla and Jyoti Sahu, "WAVELETS: BASIC CONCEPTS," International Journal of Electrical and Electronic Engineering & Telecommunications, Vol. 2, No. 4, pp. 30-36, October 2013.