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https://www.researchgate.net/publication/8345770_Wavelet_Support_Vector_Machine
Rank wavelet support vector machine (rank-WSVM) [27, 28] is proposed to apply in the classification of complex disturbances. A new method for the classification of PQ disturbances was proposed by ...
https://journals.ametsoc.org/doi/full/10.1175/WAF-D-11-00004.1
Apr 01, 2012 · In recent years, the combination of wavelet theories and SVMs, called wavelet support vector machines (WSVMs; see section 3) has drawn considerable attention owing to its high predictive ability for a wide range of applications and its better performance compared with other traditional leaning machines (Kivanc et al. 2003).Cited by: 24
https://www.mathworks.com/help/signal/examples/ecg-classification-using-wavelet-features.html
This example shows how to classify human electrocardiogram (ECG) signals using wavelet-based feature extraction and a support vector machine (SVM) classifier. The problem of signal classification is simplified by transforming the raw ECG signals into a much smaller set of features that serve in aggregate to differentiate different classes.
https://blogs.mathworks.com/headlines/2016/08/23/using-wavelet-transforms-and-machine-learning-to-predict-droughts/
Aug 23, 2016 · Many have used machine learning techniques such as artificial neural networks (ANN) and support vector regression (SVR) to train their models. In addition to machine learning, some researchers are exploring adding wavelet transforms to their models. Hybrid approaches have included wavelet-ANN (WANN) and wavelet-SVR (WSVR) models.
https://journals.sagepub.com/doi/10.1177/0263092316628258
Mar 07, 2016 · This article deals with fault detection of an alternator based on vibration signals using wavelet transform and least square support vector machine. Firstly, the noise in the vibration signal is removed using wavelet denoising. The denoised signals are then analysed using discrete wavelet transform with Daubechies mother wavelet.Cited by: 8
https://pdfs.semanticscholar.org/dbe7/bdaf11021b03eec084b4d732dcc4eac9cf5f.pdf
wavelet transform and support vector machine is set up. First, wavelet transform is applied to decompose the series into sub series with different time scales. Then, the SVM is applied to the sub series to simulate and predict future behavior. And then by the inverse wavelet transform, the
https://www.researchgate.net/profile/Liqing_Zhang3/publication/4234035_ECG_Feature_Extraction_and_Classification_Using_Wavelet_Transform_and_Support_Vector_Machines/links/5557571b08aeaaff3bf76f0c.pdf
Wavelet Transform and Support Vector Machines Qibin Zhao Department of Computer Science and Engineering Shanghai Jiaotong University Shanghai, 200030, China E-mail: [email protected]
https://dl.acm.org/doi/10.1016/j.eswa.2015.04.002
These type of events are known as complex events. The proposed Power Quality (PQ) classifier is based on Wavelet Transforms (WT) and Support Vector Machines (SVM). The method uses a One vs. One multiclass SVM. We propose a novel method which is simple, easy to train, and can be implemented with low computational cost.
https://www.sciencedirect.com/science/article/pii/S0196890414010899
In this paper, the Support Vector Machines (SVMs) and Wavelet Transform (WT) algorithm are combined to propose a new hybrid approach to predict horizontal global solar radiation. The primary aim is achieving further accuracy and reliability in estimations by taking the advantages of both approaches.Cited by: 140
https://www.sciencedirect.com/science/article/pii/S0010482511002253
In the current paper, we developed a novel method that coupled the discrete wavelet transform with support vector machine based on the amino acid polarity to predict the subcellular localizations of prokaryotic and eukaryotic proteins.Cited by: 16
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