@inproceedings{scholars1954,
             doi = {10.1109/INECCE.2011.5953904},
            year = {2011},
            note = {cited By 5; Conference of 1st International Conference on Electrical, Control and Computer Engineering 2011, InECCE 2011 ; Conference Date: 21 June 2011 Through 22 June 2011; Conference Code:85983},
           pages = {344--348},
         address = {Kuantan},
           title = {Data smoothing using Gaussian scale-space and discrete wavelet transform},
         journal = {InECCE 2011 - International Conference on Electrical, Control and Computer Engineering},
            isbn = {9781612842288},
          author = {Karim, S. A. A. and Pang, K. V.},
        abstract = {The Gaussian scale-space is widely being used in human vision problem. It can be used to smooth the data by filtering off low frequency of the signal. In this paper we will discuss the applications of Gaussian scale-space in data smoothing problem arising in financial (Kuala Lumpur Composite Index (KLCI)) and electroencephalogram (EEG) problem. We also show the comparison between Gaussian scale-space and Discrete Wavelet Transform (DWT) for data smoothing. Overall results indicated that Gaussian scale-space gave a good result. {\^A}{\copyright} 2011 IEEE.},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-80051639844&doi=10.1109\%2fINECCE.2011.5953904&partnerID=40&md5=236dff813feed6019aab29270248fa99},
        keywords = {Data smoothing; DWT; Financial data; Gaussian functions; Gaussians, Discrete wavelet transforms; Electroencephalography; Gaussian distribution, Metadata}
}