acoustic analysis is a proper method in vocal fold pathology diagnosis so that itcan complement and in some cases replace the other invasive, based on direct vocalfold observation, methods. there are different approaches and algorithms for vocalfold pathology diagnosis. these algorithms usually have three stages which arefeature extraction, feature reduction and classification. in this paper in...

Estimation of corrugation amplitude is an important but difficult point for indirect methods, to advance related research, method based on wavelet packet decomposition (WPD) and energy level wheel-rail noise developed. For this purpose, firstly, numerical models are proposed calculate under various statuses. Next, the WPD conducted noise, levels relevant nodes used as evaluation indicators ampl...

This paper presents a novel approach to induction motor current signature analysis based on wavelet packet decomposition (WPD) of the stator current. The novelty of the proposed method lies in the fact that by using WPD method the inherent nonstationary nature of stator current can be accurately considered. The key characteristics of the proposed method are its ability to provide feature repres...

Electricity price forecasting is a crucial aspect of spot trading in the electricity market and optimal scheduling microgrids. However, stochastic periodic nature sequences often results low accuracy forecasting. To address this issue, study proposes quadratic hybrid decomposition method based on ensemble empirical modal (EEMD) wavelet packet (WPD), along with deep extreme learning machine (DEL...

Introduction: Clinicians use several computer-aided diagnostic systems for depression to authorize their diagnosis. An electroencephalogram  (EEG) may be used as an objective tool for early diagnosis of depression and controlling it from reaching a severe and permanent state. However, artifact contamination reduces the accuracy in EEG signal processing systems. Methods: This work proposes a no...

As the most basic component of rotating machinery, rolling bearing frequently works in harsh environments and complex working conditions, its health status affects seriously efficiency. The statuses can not only reduce equipment maintenance costs but also contribute to reducing major accidents. Based on this, an adaptive diagnosis method that combines deep gated recurrent unit (DGRU) with wavel...

A method of and a system for speech enhancement consists of Hilbert spectrum and wavelet packet analysis is studied. We implement ISA to separate speech and interfering signals from single mixture and wavelet packet based softthresholding algorithm to enhance the quality of target speech. The mixed signal is projected onto time-frequency (TF) space using empirical mode decomposition (EMD) based...

Conventional signal processing techniques usually result in false information when they are applied to the ship mechanical fault signals, because the ship mechanical faults by nature are non-stationary and transient events. Wavelet Packet Decomposition (WPD) is a time– frequency domain technique that can be applied to non-stationary process perfectly. RBF neural network behave better than BP ne...

Ship-radiated noise (SN) is one of the most critical signals in complex marine environment; however, it inevitably contaminated by environment’s as well from other equipment. Thus, feature extraction and identification SN becomes very arduous. This paper proposes a denoising method for based on successive variational mode decomposition (SVMD), dual-threshold analysis fuzzy dispersion entropy (F...

Feature extraction and classification of electrocardiogram (ECG) signals are necessary for the automatic diagnosis of cardiac diseases. In this study, a novel method based on genetic algorithm-back propagation neural network (GA-BPNN) for classifying ECG signals with feature extraction using wavelet packet decomposition (WPD) is proposed. WPD combined with the statistical method is utilized to ...