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dc.contributor.authorWali, Mousa Kadhim
dc.contributor.authorMurugappan, M., Dr.
dc.contributor.authorR. Badlishah, Ahmad, Prof. Dr.
dc.date.accessioned2014-05-21T03:36:18Z
dc.date.available2014-05-21T03:36:18Z
dc.date.issued2012
dc.identifier.citationJournal of Mechanics in Medicine and Biology, vol. 12(5), 2012, pages 1-24en_US
dc.identifier.issn0219-5194 (Print)
dc.identifier.issn1793-6810 (Online)
dc.identifier.urihttp://www.worldscientific.com/doi/abs/10.1142/S0219519412400313
dc.identifier.urihttp://dspace.unimap.edu.my:80/dspace/handle/123456789/34562
dc.descriptionLink to publisher's homepage at http://www.worldscientific.com/en_US
dc.description.abstractIn recent years, the application of discrete wavelet transform (DWT) on biosignal processing has made a significant impact on developing several applications. However, the existing user-friendly software based on graphical user interfaces (GUI) does not allow the freedom of saving the wavelet coefficients in .txt or .xls format and to analyze the frequency spectrum of wavelet coefficients at any desired wavelet decomposition level. This work describes the development of mathematical models for the implementation of DWT in a GUI environment. This proposed software based on GUI is developed under the visual basic (VB) platform. As a preliminary tool, the end user can perform "j" level of decomposition on a given input signal using the three most popular wavelet functions-Daubechies, Symlet, and Coiflet over "n" order. The end user can save the output of wavelet coefficients either in .txt or .xls file format for any further investigations. In addition, the users can gain insight into the most dominating frequency component of any given wavelet decomposition level through fast Fourier transform (FFT). This feature is highly essential in signal processing applications for the in-depth analysis on input signal components. Hence, this GUI has the hybrid features of FFT with DWT to derive the frequency spectrum of any level of wavelet coefficient. The novel feature of this software becomes more evident for any signal processing application. The proposed software is tested with three physiological signal-electroencephalogram (EEG), electrocardiogram (ECG), and electromyogram (EMG)-samples. Two statistical features such as mean and energy of wavelet coefficient are used as a performance measure for validating the proposed software over conventional software. The results of proposed software is compared and analyzed with MATLAB wavelet toolbox for performance verification. As a result, the proposed software gives the same results as the conventional toolbox and allows more freedom to the end user to investigate the input signal.en_US
dc.language.isoenen_US
dc.publisherWorld Scientific Publishing Co. Pte Ltden_US
dc.subjectDiscrete wavelet transform (DWT)en_US
dc.subjectFast Fourier transform (FFT)en_US
dc.subjectGraphical user interface (GUI)en_US
dc.titleMathematical implementation of hybrid fast fourier transform and discrete wavelet transform for developing graphical user interface using visual basic for signal processing applicationsen_US
dc.typeArticleen_US
dc.identifier.url10.1142/S0219519412400313
dc.contributor.urlmusawali@yahoo.comen_US
dc.contributor.urlmurugappan@unimap.edu.myen_US
dc.contributor.urlbadli@unimap.edu.myen_US


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