Comparison of STFT and Wavelet Transform inTime-frequency Analysis

by Pu Sun

Institution: Högskolan i Gävle
Year: 2015
Keywords: short time Fourier transform; wavelet transform; Engineering and Technology; Electrical Engineering, Electronic Engineering, Information Engineering; Signal Processing; Teknik och teknologier; Elektroteknik och elektronik; Signalbehandling; Elektronik – kandidatprogram (på eng); Electronics – bachelor’s programme (in eng); Electronics; Elektronik
Record ID: 1348255
Full text PDF: http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-19072


The wavelet transform technique has been frequently used in time-frequency analysis as a relatively new concept. Compared to the traditional technique Short-time Fourier Transform (STFT), which is theoretically based on the Fourier transform, the wavelet transform has its advantage on better locality in time and frequency domain, but not significant as the solutions in spectrum. Wavelet transform has dynamic ‘window functions’ to represent time-frequency positions of raw signals, and can get better resolutions in time-frequency analysis. In this report, we shall first briefly introduce fuzzy sets and related concepts. And then we will evaluate their similarities and differences by not only the theoretic comparisons between STFT and wavelet transform, but also the process of the de-nosing to a noisy recorded signal.