TY  - JOUR
JF  - Applied Mathematical Sciences
A1  - Karim, S.A.A.
A1  - Ismail, M.T.
A1  - Hasan, M.K.
A1  - Sulaiman, J.
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886739036&doi=10.12988%2fams.2013.38450&partnerID=40&md5=99e3f449258aa7da1c6cc726e73597d1
EP  - 5830
VL  - 7
Y1  - 2013///
SN  - 1312885X
IS  - 117-12
N2  - Wavelets transform are effectively used in data compression and denoising such as in signal and image compression and denoising. One of the advantages of wavelets method is there exist fast algorithm in order to use wavelet for various applications. In this paper we will apply Discrete Wavelet Transform (DWT) to denoise the temperature data using symlet 16 with 32 corresponding filters (low-pass and high-pass). We apply various thresholding approaches e.g., Heuristic SURE, SURE, Minimax and Fixed-Form method. We utilized temperature data in Kuala Lumpur from January 1948 until July 2010. We also discuss the advantages of wavelet as compared with Fast Fourier Transform (FFT). Several numerical results will be presented by using Matlab. © 2013 Samsul Ariffin Abdul Karim et al.
N1  - cited By 6
SP  - 5821
ID  - scholars3365
TI  - Denoising the temperature data using wavelet transform
AV  - none
ER  -