A Pyramid Algorithm For The Haar Discrete Wavelet Packet Transform

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dc.contributor.authorLuhanga, Edith T.
dc.contributor.authorLuhanga, Matthew L.
dc.date.accessioned2016-02-19T06:25:07Z
dc.date.available2016-02-19T06:25:07Z
dc.date.issued2013-10
dc.description.abstractOne area of application of the discrete wavelet transform (DWT) has been the detection and classification of physiological signals such as electroencephalography (EEG) signals. Anomalies in EEGs yield very low frequency signals which are ideal for analysis using the DWT. Anomalies in mechanical systems yield high frequency signals. The structure of the DWT makes it an un-ideal tool for the analysis of such signals. Such signals are, however, ideal for analysis using the wavelet packet transform (WPT) in which Mallat’s pyramid algorithm is applied to the multiresolution analysis (MRA) of both the approximation and detail subspaces of a signal. As a contribution to the computer-aided signal processing of non-stationary signals, this paper develops a pyramid algorithm for the discrete wavelet packet transform (DWPT) from two-scale relations for wavelet packets. The algorithm is used in the derivation of the fast Haar discrete wavelet packet transform (FHDWPT) and its inverse. It is found out that the FHDWPT is computationally as efficient as the fast Fourier transform (FFT).en_US
dc.identifier.citationEdith T. Luhanga and Matthew L. Luhanga, “A Pyramid Algorithm for the Haar Disrete Wavelet Packet Transform”. Submitted to The Global Journal of Engineering Research in October, 2013.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/447
dc.language.isoenen_US
dc.publisherBachudo Science Co. Ltden_US
dc.subjectWaveleten_US
dc.subjectPacketsen_US
dc.subjectHaaren_US
dc.subjectPyramiden_US
dc.subjectAlgorithmen_US
dc.titleA Pyramid Algorithm For The Haar Discrete Wavelet Packet Transformen_US
dc.typeConference Paperen_US
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