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7 results for “intrinsic mode function”
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Research ArticleOpen accessIn the keywordsLung Sound Classification Using Empirical Mode Decomposition and the Hjorth DescriptorAchmad Rizal, Risanuri Hidayat, Hanung Adi NugrohoLung sound is produced by the respiration process in the human respiratory tract. It contains information about the health of the respiratory organs. Lung sound is non-stationary signals and complex signals. One method for the analysis of non-stationary signals often used for the analysis of lung sounds is Empirical Mode Decomposition (EMD). EMD is used to view the Instantaneous Frequency … …American Journal of Applied Sciences, Vol. 14, Issue 1 · 27 Jan 2017 · 8,194 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHeart Rate Variability Analysis in Different Age and Pathological ConditionsM.E.S. Chelladurai, N. KumaravelProblem statement: Heart Rate Variability (HRV) has been used as a measure of mortality primarily with patients who had undergone cardiac surgery. The analysis of Heart Rate Variability (HRV) demands specific capabilities which are not provided either by parametric or nonparametric conventional estimation methods. The Empirical Mode Decomposition (EMD) adaptively estimates the Intrinsic Mode Functions (IMFs) of nonlinear nonstationary signals. … …Journal of Computer Science, Vol. 7, Issue 10 · 4 Aug 2011 · 6,818 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementing a Hybrid VMD–BiTCN–BiGRU Architecture With Intelligent Optimization for Agricultural Commodity Price Prognostication in Gujarat MarketsJignesh Hirapara, Ratnesh Kumar Namdeo, Ankit Kumar Dubey et al.In the agricultural sector, the prices of pulses require adequate forecasting to plan farming activities, store and market, and guide policy-making. However, the pulse price series is highly volatile, seasonal, nonstationary, and nonlinear, and thus conventional linear time series models are not necessarily very effective. In the suggested framework, the raw price data series is decomposed using Variational Mode Decomposition … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Aug 2026 · 1,021 accessesView PDFCite
Research ArticleOpen accessIn the abstractEpileptic Seizure Detection Using Integrated Decomposed Features from EEG SignalShupta Das, Suraiya Akter Mumu, M. A. H. Akhand, Md Abdus Samad KamalThe root cause of the seizure is a sudden abnormal excessive electrical discharge in the brain and it is an Epileptic Seizure (ES) when such abnormal electrical activity arises particularly for epilepsy. Recognizing ES is crucial for effective treatment as it often repeats and can lead to serious outcomes. Since epilepsy is a neurological issue, detecting ES by analyzing brain … …Journal of Computer Science, Vol. 20, Issue 10 · 8 Aug 2024 · 4,845 accessesView PDFCite
Research ArticleOpen accessIn the abstractMetabolic Potential Versus Genome SizeAtanas Todorov Atanasov, Dimitar Todorov ValevAlberch, P. (1983). Development and Evolution: Embryos, Genes, and Evolution. The Developmental-Genetic Basis of Evolutionary Change. Science, 221(4607), 257–258. https://doi.org/10.1126/science.221.4607.257 Andrews, C. B., Mackenzie, S. A., & Gregory, T. R. (2009). Genome size and wing parameters in passerine birds. Proceedings of the Royal Society B, 276(1654), 55–61. https://doi.org/10.1098/rspb.2008.1012 Atanasov, A. T. (2005). The linear alometric relationship between total metabolic energy … …Physics International, Vol. 13, Issue 1 · 15 Jun 2022 · 7,229 accessesView PDFCite
Research ArticleOpen accessIn the abstractECG Energy Change Study Based on Variational Mode DecompositionKai Dong, Lin Sun, Hongjun Xiong, Wenbo WangVariational Mode Decomposition (VMD) decomposes the signal into a series of Intrinsic Mode Type Functions (IMTFs) according with variational model and fluctuating characteristics of the signal itself, thus very suitable for the analysis of nonlinear and non-stationary Electrocardiogram (ECG) signal. Energy of ECG signal has certain distribution rules, but which could be affected by diseases; therefore, the study of ECG … …American Journal of Biochemistry and Biotechnology, Vol. 16, Issue 1 · 12 Mar 2020 · 7,397 accessesView PDFCite
Research ArticleOpen accessIn the abstractHydrological Forecasting Using Hybrid Data-Driven ApproachYoungmin Seo, Sungwon KimThis study develops a hybrid model, EEMD-FANN, coupling feed Forward Artificial Neural Network (FANN) and Ensemble Empirical Mode Decomposition (EEMD) for improving the accuracy of daily river stage forecasting. An original river stage data is broken down into a residue and Intrinsic Mode Functions (IMFs) using the EEMD and different FANNs are developed as forecasting models for the decomposed IMFs … …American Journal of Applied Sciences, Vol. 13, Issue 8 · 2 Sep 2016 · 8,136 accessesView PDFCite