Multilevel wavelet packet entropy: A new strategy for lung sound feature extraction based on wavelet entropy
Penulis/Author
ACHMAD RIZAL (1); Prof. Dr. Ir. Risanuri Hidayat, M.Sc., IPM. (2); Prof. Ir. Hanung Adi Nugroho, S.T., M.Eng., Ph.D., IPM., SMIEEE. (3)
Tanggal/Date
29 2017
Kata Kunci/Keyword
Abstrak/Abstract
Wavelet packet entropy (WPE) is one of the entropy measurement methods based on wavelet transform. If wavelet entropy (WE) is used in discrete wavelet transform (DWT), then WPE used wavelet packet decomposition (WPD) for entropy calculation. Various entropy measurement techniques are used in WPE calculations and generate 2N parameters where N refers to the decomposition level. In this paper, we proposed a new method based on WPE called multilevel wavelet packet entropy (MWPE). With the proposed method, the number of parameters produced is N, the wavelet decomposition level. The accuracy up to 97.98% was obtained for five classes of lung sound. The proposed method yielded accuracy higher than the use of one decomposition level in WPE. This method can also be used for the features extraction of the biological signals such as electrocardiogram (ECG), or electroencephalogram (EEG).
Level
Internasional
Status
Dokumen Karya
No
Judul
Tipe Dokumen
Aksi
1
2017 Multilevel wavelet packet entropy A new strategy for lung sound feature extraction based on wavelet entropy.pdf
