Lung Sound Classification Using Empirical Mode Decomposition and the Hjorth Descriptor
نویسندگان
چکیده
منابع مشابه
Reduction of heart sound interference from lung sound signals using empirical mode decomposition technique.
During the recording time of lung sound (LS) signals from the chest wall of a subject, there is always heart sound (HS) signal interfering with it. This obscures the features of lung sound signals and creates confusion on pathological states, if any, of the lungs. A novel method based on empirical mode decomposition (EMD) technique is proposed in this paper for reducing the undesired heart soun...
متن کاملSignal Detection in Underwater Sound Using the Empirical Mode Decomposition
In this article, the empirical mode decomposition (EMD) is introduced to the problem of signal detection in underwater sound. EMD is a new method pioneered by Huang et al. for non-linear and nonstationary signal analysis. Based on the EMD, any input data can be decomposed into a small number of intrinsic mode functions (IMFs) which can serve as the basis of non-stationary data for they are comp...
متن کاملClassification of Features of Pavement Profiles Using Empirical Mode Decomposition
The Long-Term Pavement Performance (LTPP) database contains surface profile data for numerous pavements that are used mainly for computing International Roughness Index (IRI).(2) In order to obtain more information from these surface profiles, a Hilbert-Huang Transform (HHT) based surface profile algorithm was developed to analyze LTPP field road profile data in order to extract smoothed, consi...
متن کاملPathological Voice Analysis and Classification Based on Empirical Mode Decomposition
Empirical mode decomposition (EMD) is an algorithm for signal analysis recently introduced by Huang. It is a completely datadriven non-linear method for the decomposition of a signal into AM FM components. In this paper two new EMD-based methods for the analysis and classification of pathological voices are presented. They are applied to speech signals corresponding to real and simulated sustai...
متن کاملShort Term Load Forecasting Using Empirical Mode Decomposition, Wavelet Transform and Support Vector Regression
The Short-term forecasting of electric load plays an important role in designing and operation of power systems. Due to the nature of the short-term electric load time series (nonlinear, non-constant, and non-seasonal), accurate prediction of the load is very challenging. In this article, a method for short-term daily and hourly load forecasting is proposed. In this method, in the first step, t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: American Journal of Applied Sciences
سال: 2017
ISSN: 1546-9239
DOI: 10.3844/ajassp.2017.166.173