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Search results for: wavelet
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Year: 2023, Volume: 23, Number: 2
... as small as possible and contains the maximum amount of wavelet transform method for obtaining the time-frequency relevant information to ... (Table II). For the binary problem, Wavelet_db4_EnergyBand1, Wavelet_db4_EnergyBand2, two classes are used to predict ... ongoing seizures by a Wavelet_db4_EnergyBand3, Wavelet_db4_EnergyBand4, supervised binary classifier. The pre-ictal is used as the Wavelet_db4_EnergyBand5} ...
Year: 2023, Volume: 23, Number: 1
... . such as STRRED [30]. STRRED uses Gaussian scale The media-layer models use audio or video signals to mixture (GSM) to model the statistics of wavelet evaluate QoE. These models do not require any prior coefficients and compute the entropic differences (RRED) knowledge about the system under consideration, such as between ...
Year: 2022, Volume: 22, Number: 4
... 4] A. D. Spyronasios, M. G. Dimopoulos, and A. A. Hatzopoulos, analog circuit fault diagnosis using 1-D convolutional neural "Wavelet Analysis for the detection of parametric and catastrophic network," IEEE Access, vol. 8, pp. 18305 – 18315, 2020. faults in mixed-signal ...
Year: 2022, Volume: 22, Number: 3
... of application, an object detection algorithm should be and feature computation use the Haar wavelet [13]. invariant to some photometric, geometric, and affine On ... there are [13] P. Porwik, A. Lisowska, "The Haar-wavelet transform in digital image processing: its status and achievements," Machine graphics ...
Year: 2022, Volume: 22, Number: 2
... To reduce the adverse effects of the inherent methods contain Empirical Mode Decomposition (EMD) [1- stochastic volatility and uncontrollability of new energy on 2] and Wavelet decomposition (WD) [3-4], multi-factor wind energy forecasting, this paper starting from the two PCA analysis [5 ], and so on. ...
Year: 2022, Volume: 22, Number: 1
... , H. Chen, "Time series prediction of wireless Things (IoT): Smart home context," Journal of Computer Information network traffic flow based on wavelet analysis and BP neural Systems, vol. 60, no. 6, Nov. 2020, pp. 507 – 517. network," Journal of ...
Year: 2022, Volume: 22, Number: 1
... forgery. detect a forgery in the presence of blurring and contrast Different classifiers have been exercised in the literature enhancement. Wu et al., used Dual-Tree Complex Wavelet for different applications in the various fields of life. For transform (DT-CWT) to detect image forgeries [19]. example SVM classifier has been used ...
Year: 2021, Volume: 21, Number: 4
... refers to the reconstruction of magnetic resonance exploiting the sparsity of sparsifying transform (e.g., images from partially sampled k-space data. The k-space data Discrete Cosine or wavelet transform) and incoherent reduces reconstruction processing time but at the cost of sampling methods. The physical limitations of MRI slow increasing artifacts- especially with the higher ...
Year: 2021, Volume: 21, Number: 4
... and application of the SVM algorithm. 1 N N 1 Network Scan Another approach estimates the applicability of the two- 1 N N N Diagonal Scan level stationary wavelet entropy (SWE) method to extract N 1 1 1 Amplification DDoS (DNS) N 1 1 N Amplification DDoS (NTP) specific features and apply ...
Year: 2021, Volume: 21, Number: 4
... related technical summary for the following hybrid forecasting scheme: First, high frequency denoising of four categories: based on physical information, mining wind power sequence using synchrosqueezed wavelet information by statistical methods, the application of transforms (SWT), reducing the influence of noise on intelligent algorithms, and combined models. At present, ...
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