Topic
Symlet
About: Symlet is a research topic. Over the lifetime, 271 publications have been published within this topic receiving 2374 citations.
Papers published on a yearly basis
Papers
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TL;DR: A novel approach for generating the wavelet that best represents the ECG beats in terms of discrimina- tion capability is proposed, which makes use of the polyphase representation of the wavelets filter bank and formulates the design problem within a particle swarm optimization (PSO) framework.
161 citations
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TL;DR: In this article, the results of the above fusion methods were compared and comments on the fusion methods and the potential of evaluation indicators were made, including two-dimensional correlation, relative difference of means, relative variation, deviation index, entropy difference, peak signal-to-noise ratio index and universal image quality index, as well as photo-interpretation methods and techniques.
Abstract: Various fusion methods have been developed for improving data spatial resolution. The methods most encountered in the literature are the intensity-hue-saturation (IHS) transform, the Brovey transform, the principal components algorithm (PCA) fusion method, the Gram-Schmidt fusion method, the local mean matching method, the local mean and variance matching method, the least square fusion method, the discrete wavelet fusion method including Daubechies, Symlet, Coiflet, biorthogonal spline, reverse biorthogonal spline, and Meyer wavelets, the wavelet-PCA fusion method, and the crossbred IHS and wavelet fusion method. Using various evaluation indicators such as two-dimensional correlation, relative difference of means, relative variation, deviation index, entropy difference, peak signal-to-noise ratio index and universal image quality index, as well as photo-interpretation methods and techniques, results of the above fusion methods were compared and comments on the fusion methods and potential of evaluation indicators were made. Among data fusion methods and indicators the local mean and variance matching methods proved the most efficient and the peak signal-to-noise ratio indicator proved the most appropriate for the evaluation of data fusion results.
149 citations
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TL;DR: This study comprehensively evaluated the multi-step prediction performance of models with different denoising algorithms using the traffic volume data collected from three loop detectors located on highway in city of Minneapolis to propose a prediction method by combiningDenoising schemes and support vector machine model to improve prediction accuracy.
Abstract: Traffic flow prediction with high accuracy is definitely considered as one of most important parts in the Intelligent Transportation Systems. As interfering by some external factors, the raw traffic flow data containing noise may cause decline of prediction performance. This study proposes a prediction method by combining denoising schemes and support vector machine model to improve prediction accuracy. This study comprehensively evaluated the multi-step prediction performance of models with different denoising algorithms using the traffic volume data collected from three loop detectors located on highway in city of Minneapolis. In the prediction performance comparison, five denoising methods including EMD (Empirical Mode Decomposition), EEMD (Ensemble Empirical Mode Decomposition), MA (Moving Average), BW filter (Butterworth) and WL (Wavelet) are considered as candidates, specially, four wavelet types, coif (coiflet), db (daubechies), haar and sym (symlet), are further compared based on accuracy evaluation indicators. The prediction results show that the prediction results of the model combined with denoising algorithm are better that of the model without denoising strategy. Furthermore, the improvement of the EEMD on prediction performance is higher than other denoising algorithms, and WL method with db type achieves higher accuracy than other three types. Through comparing prediction accuracy of different denoising models, this study provides valuable suggestions for selecting the appropriate denoising approach for traffic flow prediction.
134 citations
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TL;DR: A novel modified S-median thresholding technique is proposed and evaluated for denoising ECG signal and showed that the proposed system performed better than S- median and other existing techniques in the time domain.
119 citations
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TL;DR: In this paper, a hybrid model that couples discrete wavelet transforms (WT) and artificial neural networks (ANN) is proposed for forecasting water temperature, which is applied to forecast daily water temperature on the Warta River in Poland.
108 citations