Wavelet packet transform, a reliable and fast method to obtain the fundamental components required for active filtering in power plants

Nicolae, Ileana-Diana; Nicolae, Petre-Marian; Smarandescu, Ionut-Daniel; Nicolae, Marian-Stefan

doi:10.1109/epepemc.2016.7752116

Cited by 9 publications

(3 citation statements)

References 7 publications

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“…The scaling PWT coefficients are denoted as γ l 2p and PWT wavelet coefficients are labeled as γ l 2p+1 , as shown in the expressions below [28],…”

Section: Wavelet and Packet-wavelet Transformmentioning

confidence: 99%

See 1 more Smart Citation

A Proposed Channel Estimation Based on Enhanced Sub-carrier Index Modulation and Packet-Discrete Wavelet Transform to Minimize Bit Error Rate

Jabbar¹

2021

ETJ

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“…The scaling PWT coefficients are denoted as γ l 2p and PWT wavelet coefficients are labeled as γ l 2p+1 , as shown in the expressions below [28],…”

Section: Wavelet and Packet-wavelet Transformmentioning

confidence: 99%

“…Each sub-band covers one-sixteenth of the signal frequency spectrum, resulting in a total of 16 sub-bands with a four-level PWT. PWT is an appealing method for detecting and classifying high-frequency transients due to its improved signal decomposition capacity [28].…”

Section: Wavelet and Packet-wavelet Transformmentioning

confidence: 99%

A Proposed Channel Estimation Based on Enhanced Sub-carrier Index Modulation and Packet-Discrete Wavelet Transform to Minimize Bit Error Rate

Jabbar¹

2021

ETJ

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“…The authors have previously studied a specific type of WT called Wavelet Packet Transform (WPT) that was proposed in 1992 [3]. WPT provides full harmonic spectrum but suffers from decimation phenomenon [4]- [7]. Detailed analysis of wavelet binary tree shown the best parameters (number of levels, wavelet mother, filter length) when applying WT.…”

Section: Introductionmentioning

confidence: 99%

Analyzing the Influence of Harmonic Parameters on Accuracy Indices When Applying Wavelet Transform

Kostic¹,

Nicolae²,

Nuca³

et al. 2021

AUCEE

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The paper deals with the evaluation of root mean square deviations and maximum absolute relative errors associated to the decomposition followed by recomposition based on Wavelet Packet Transform (WPT) of signals pol-luted with harmonics. Subtrees associated to sets of harmonics presenting practical interest for industrial applications are addressed. The study uses artificial signals generated through the superposition of perfect sinusoids with pairs of harmonics which proved to be related in an almost exclusive manner to pairs of nodes from the bottom level of a WPT tree. 4 parameters had to be considered when determining the maximum and minimum values of errors for each set: the clustered harmonics’ magnitudes and their phase-shifts relative to the component of fundamental frequency. The decomposition/recomposition are time-efficient due to an original system of flags labeling each node from the WPT tree. For each analyzed set of harmonics, 3d graphical representation of minimum and maximum errors along with the associated 3d graphical representation of the phase-shifts are provided. At the same time, per set limits of errors ranges were established and discussed while specific patterns were deduced for the context in which extreme errors appear (phase-shifts and harmonic magnitudes). The results were commented, and conclusions were drawn.

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Dealing with linearly variable magnitudes in fourier and wavelet packet transform frameworks

Nicolae

Maria

et al. 2016

2016 International Conference on Applied and Theoretical Electricity (ICATE)

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Wavelet packet transform, a reliable and fast method to obtain the fundamental components required for active filtering in power plants

Cited by 9 publications

References 7 publications

A Proposed Channel Estimation Based on Enhanced Sub-carrier Index Modulation and Packet-Discrete Wavelet Transform to Minimize Bit Error Rate

A Proposed Channel Estimation Based on Enhanced Sub-carrier Index Modulation and Packet-Discrete Wavelet Transform to Minimize Bit Error Rate

Analyzing the Influence of Harmonic Parameters on Accuracy Indices When Applying Wavelet Transform

Dealing with linearly variable magnitudes in fourier and wavelet packet transform frameworks

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