Wavelet transform ≈ Wavelet transform
View article
Classification using deep learning neural networks for brain tumors Open
Deep Learning is a new machine learning field that gained a lot of interest over the past few years. It was widely applied to several applications and proven to be a powerful machine learning tool for many of the complex problems. In this …
View article
Wavelet Transform Application for/in Non-Stationary Time-Series Analysis: A Review Open
Non-stationary time series (TS) analysis has gained an explosive interest over the recent decades in different applied sciences. In fact, several decomposition methods were developed in order to extract various components (e.g., seasonal, …
View article
Secure Medical Data Transmission Model for IoT-Based Healthcare Systems Open
Due to the significant advancement of the Internet of Things (IoT) in the healthcare sector, the security, and the integrity of the medical data became big challenges for healthcare services applications. This paper proposes a hybrid secur…
View article
ECG Classification Using Wavelet Packet Entropy and Random Forests Open
The electrocardiogram (ECG) is one of the most important techniques for heart disease diagnosis. Many traditional methodologies of feature extraction and classification have been widely applied to ECG analysis. However, the effectiveness a…
View article
A Review of Wavelet Analysis and Its Applications: Challenges and Opportunities Open
As a general and rigid mathematical tool, wavelet theory has found many applications and is constantly developing. This article reviews the development history of wavelet theory, from the construction method to the discussion of wavelet pr…
View article
Deep Learning Enabled Fault Diagnosis Using Time-Frequency Image Analysis of Rolling Element Bearings Open
Traditional feature extraction and selection is a labor-intensive process requiring expert knowledge of the relevant features pertinent to the system. This knowledge is sometimes a luxury and could introduce added uncertainty and bias to t…
View article
Classification of Heart Sound Signal Using Multiple Features Open
Cardiac disorders are critical and must be diagnosed in the early stage using routine auscultation examination with high precision. Cardiac auscultation is a technique to analyze and listen to heart sound using electronic stethoscope, an e…
View article
DWT Based Detection of Epileptic Seizure From EEG Signals Using Naive Bayes and k-NN Classifiers Open
Electroencephalogram (EEG) comprises valuable details related to the different physiological state of the brain. In this paper, a framework is offered for detecting the epileptic seizures from EEG data recorded from normal subjects and epi…
View article
Ensemble SVM Method for Automatic Sleep Stage Classification Open
Sleep scoring is used as a diagnostic technique in the diagnosis and treatment of sleep disorders. Automated sleep scoring is crucial, since the large volume of data should be analyzed visually by the sleep specialists which is burdensome,…
View article
Emotion Recognition from EEG Signals Using Multidimensional Information in EMD Domain Open
This paper introduces a method for feature extraction and emotion recognition based on empirical mode decomposition (EMD). By using EMD, EEG signals are decomposed into Intrinsic Mode Functions (IMFs) automatically. Multidimensional inform…
View article
Brain MRI Image Classification for Cancer Detection Using Deep Wavelet Autoencoder-Based Deep Neural Network Open
Technology and the rapid growth in the area of brain imaging technologies have forever made for a pivotal role in analyzing and focusing the new views of brain anatomy and functions. The mechanism of image processing has widespread usage i…
View article
Facial Emotion Recognition Based on Biorthogonal Wavelet Entropy, Fuzzy Support Vector Machine, and Stratified Cross Validation Open
Emotion recognition represents the position and motion of facial muscles. It contributes significantly in many fields. Current approaches have not obtained good results. This paper aimed to propose a new emotion recognition system based on…
View article
A Novel Fault Diagnosis Method Based on Integrating Empirical Wavelet Transform and Fuzzy Entropy for Motor Bearing Open
Motor bearing is subjected to the joint effects of much more loads, transmissions, and shocks that cause bearing fault and machinery breakdown. A vibration signal analysis method is the most popular technique that is used to monitor and di…
View article
Multi-Level Wavelet Convolutional Neural Networks Open
In computer vision, convolutional networks (CNNs) often adopt pooling to enlarge receptive field which has the advantage of low computational complexity. However, pooling can cause information loss and thus is detrimental to further operat…
View article
HeartID: A Multiresolution Convolutional Neural Network for ECG-Based Biometric Human Identification in Smart Health Applications Open
Body area networks, including smart sensors, are widely reshaping health applications in the new era of smart cities. To meet increasing security and privacy requirements, physiological signalbased biometric human identification is gaining…
View article
Automatic ECG Classification Using Continuous Wavelet Transform and Convolutional Neural Network Open
Early detection of arrhythmia and effective treatment can prevent deaths caused by cardiovascular disease (CVD). In clinical practice, the diagnosis is made by checking the electrocardiogram (ECG) beat-by-beat, but this is usually time-con…
View article
A New Wavelet Denoising Method for Selecting Decomposition Levels and Noise Thresholds Open
A new method is presented to denoise 1-D experimental signals using wavelet transforms. Although the state-of- the-art wavelet denoising methods perform better than other denoising methods, they are not very effective for experimental sign…
View article
Wind Power Short-Term Prediction Based on LSTM and Discrete Wavelet Transform Open
A wind power short-term forecasting method based on discrete wavelet transform and long short-term memory networks (DWT_LSTM) is proposed. The LSTM network is designed to effectively exhibit the dynamic behavior of the wind power time seri…
View article
A Machine Learning-Based Big EEG Data Artifact Detection and Wavelet-Based Removal: An Empirical Approach Open
The electroencephalogram (EEG) signals are a big data which are frequently corrupted by motion artifacts. As human neural diseases, diagnosis and analysis need a robust neurological signal. Consequently, the EEG artifacts’ eradication is a…
View article
A wavelet-based technique to predict treatment outcome for Major Depressive Disorder Open
Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant's treatment outcome may help during antidepressant's selection and ultimately improve th…
View article
A Novel Fault Diagnosis Method for Rotating Machinery Based on a Convolutional Neural Network Open
Fault diagnosis is critical to ensure the safety and reliable operation of rotating machinery. Most methods used in fault diagnosis of rotating machinery extract a few feature values from vibration signals for fault diagnosis, which is a d…
View article
A high-performance seizure detection algorithm based on Discrete Wavelet Transform (DWT) and EEG Open
In the past decade, Discrete Wavelet Transform (DWT), a powerful time-frequency tool, has been widely used in computer-aided signal analysis of epileptic electroencephalography (EEG), such as the detection of seizures. One of the important…
View article
A multi-biometric iris recognition system based on a deep learning approach Open
Multimodal biometric systems have been widely applied in many real-world applications due to its ability to deal with a number of significant limitations of unimodal biometric systems, including sensitivity to noise, population coverage, i…
View article
Regional soil organic carbon prediction model based on a discrete wavelet analysis of hyperspectral satellite data Open
Most studies have the achieved rapid and accurate determination of soil organic carbon (SOC) using laboratory spectroscopy; however, it remains difficult to map the spatial distribution of SOC. To predict and map SOC at a regional scale, w…
View article
Wavelet Transform Time-Frequency Image and Convolutional Network-Based Motor Imagery EEG Classification Open
Feature extraction and classification play an important role in brain–computer interface (BCI) systems. In traditional approaches, methods in pattern recognition field are adopted to solve these problems. Nowadays, the deep learning theory…
View article
Electroencephalography Based Fusion Two-Dimensional (2D)-Convolution Neural Networks (CNN) Model for Emotion Recognition System Open
The purpose of this study is to improve human emotional classification accuracy using a convolution neural networks (CNN) model and to suggest an overall method to classify emotion based on multimodal data. We improved classification perfo…
View article
A Robust 3-D Medical Watermarking Based on Wavelet Transform for Data Protection Open
In a telemedicine diagnosis system, the emergence of 3D imaging enables doctors to make clearer judgments, and its accuracy also directly affects doctors’ diagnosis of the disease. In order to ensure the safe transmission and storage of me…
View article
The Forecasting of PM2.5 Using a Hybrid Model Based on Wavelet Transform and an Improved Deep Learning Algorithm Open
In recent years, the haze has caused serious troubles to people's lives, with the continuous increase of PM2.5 emissions. The accurate prediction of PM2.5 is very crucial for policy makers to make predictive measures. Due to the nonlineari…
View article
Element analysis: a wavelet-based method for analysing time-localized events in noisy time series Open
A method is derived for the quantitative analysis of signals that are composed of superpositions of isolated, time-localized ‘events’. Here, these events are taken to be well represented as rescaled and phase-rotated versions of generalize…
View article
A Novel Deep Learning Approach With Data Augmentation to Classify Motor Imagery Signals Open
Brain-computer interface provides a new communication bridge between the human mind and devices, depending largely on the accurate classification and identification of non-invasive EEG signals. Recently, the deep learning approaches have b…