AIMC Topic: Wavelet Analysis
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Fuzzy wavelet plus a quantum neural network as a design base for power system stability enhancement.
Neural networks : the official journal of the International Neural Network Society
Aug 1, 2015
In this study, we introduce an indirect adaptive fuzzy wavelet neural controller (IAFWNC) as a power system stabilizer to damp inter-area modes of oscillations in a multi-machine power system. Quantum computing is an efficient method for improving th...
Predicting Complete Ground Reaction Forces and Moments During Gait With Insole Plantar Pressure Information Using a Wavelet Neural Network.
Journal of biomechanical engineering
Jul 1, 2015
In general, three-dimensional ground reaction forces (GRFs) and ground reaction moments (GRMs) that occur during human gait are measured using a force plate, which are expensive and have spatial limitations. Therefore, we proposed a prediction model ...
ECG Prediction Based on Classification via Neural Networks and Linguistic Fuzzy Logic Forecaster.
TheScientificWorldJournal
Jun 29, 2015
The paper deals with ECG prediction based on neural networks classification of different types of time courses of ECG signals. The main objective is to recognise normal cycles and arrhythmias and perform further diagnosis. We proposed two detection s...
A novel method for discrimination between innocent and pathological heart murmurs.
Medical engineering & physics
May 21, 2015
This paper presents a novel method for discrimination between innocent and pathological murmurs using the growing time support vector machine (GTSVM). The proposed method is tailored for characterizing innocent murmurs (IM) by putting more emphasis o...
Initialization by a novel clustering for wavelet neural network as time series predictor.
Computational intelligence and neuroscience
Apr 22, 2015
The architecture and parameter initialization of wavelet neural network are discussed and a novel initialization method is proposed. The new approach can be regarded as a dynamic clustering procedure which will derive the neuron number as well as the...
Automatic detection of atrial fibrillation using stationary wavelet transform and support vector machine.
Computers in biology and medicine
Mar 14, 2015
BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia, and a major public health burden associated with significant morbidity and mortality. Automatic detection of AF could substantially help in early diagnosis, management and co...
Automated system for lung nodules classification based on wavelet feature descriptor and support vector machine.
Biomedical engineering online
Feb 12, 2015
BACKGROUND: Lung cancer is a leading cause of death worldwide; it refers to the uncontrolled growth of abnormal cells in the lung. A computed tomography (CT) scan of the thorax is the most sensitive method for detecting cancerous lung nodules. A lung...
Humans
Algorithms
Tomography, X-Ray Computed
Radiographic Image Interpretation, Computer-Assisted
Lung Neoplasms
Support Vector Machine
Referral and Consultation
Sensitivity and Specificity
Solitary Pulmonary Nodule
Automation
Pattern Recognition, Automated
ROC Curve
Area Under Curve
Wavelet Analysis
Imaging, Three-Dimensional
Incidental Findings
Automatic detection of sleep apnea based on EEG detrended fluctuation analysis and support vector machine.
Journal of clinical monitoring and computing
Feb 8, 2015
Sleep apnea syndrome (SAS) is prevalent in individuals and recently, there are many studies focus on using simple and efficient methods for SAS detection instead of polysomnography. However, not much work has been done on using nonlinear behavior of ...
Feature extraction and classification for EEG signals using wavelet transform and machine learning techniques.
Australasian physical & engineering sciences in medicine
Feb 4, 2015
This paper describes a discrete wavelet transform-based feature extraction scheme for the classification of EEG signals. In this scheme, the discrete wavelet transform is applied on EEG signals and the relative wavelet energy is calculated in terms o...
A Novel Method for Automated Diagnosis of Epilepsy Using Complex-Valued Classifiers.
IEEE journal of biomedical and health informatics
Jan 6, 2015
The study reported herein proposes a new method for the diagnosis of epilepsy from electroencephalography (EEG) signals based on complex classifiers. To carry out this study, first the features of EEG data are extracted using a dual-tree complex wave...
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