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Search results for: wavelet
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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: 2017, Volume: 17, Number: 3
... . A speed controller using a considered an advantage. This allows for operating above wavelet-neural-network of IPMSM drives was designed the rated speed at constant voltage. This enables ... A. Khan, M.N. Uddin, M.A. Rahman, "A Novel Wavelet-Neural- 29 – Dec. 2, 2001, vol. 2, pp ...
Year: 2013, Volume: 13, Number: 4
... improve the compressive image Index Terms — compressive sensing, combined sparsifying fusion results. Three different sparsifying transforms: the transforms, image fusion. spatial finite-difference, the wavelet and the contourlet are employed for sparsely representing different features of I. INTRODUCTION images. As a consequence, the reconstruction model Compressive sensing (CS) [ ...
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, ...
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: 2017, Volume: 17, Number: 3
... signal paper is to present an affordable real-time power quality processing and machine learning methods. Digital signal classification methodology by using a simplified ST scheme processing techniques such as Wavelet Transforms (WT) [1- with the platform independent hardware and software. 5] and ST [2 ], [6-14] have a widespread ...
Year: 2019, Volume: 19, Number: 2
... of one broken rotor bar in the induction motor techniques namely, Fast Fourier Transform (FFT), Discrete during the startup and steady state conditions of operation. Wavelet Transform (DWT), Empirical Mode Index Terms — induction motors, fault diagnosis, rotors, Decomposition (EMD), and some others for MCSA analysis ...
Year: 2021, Volume: 21, Number: 1
... for both gray and Examples of such transforms are the Fourier transform (FT) color images. The results are comparable to those of most [23], wavelet transform (WT) [24], and discrete cosine recent studies. transform (DCT) [25], [26]. From the information-loss ...
Year: 2017, Volume: 17, Number: 2
... --- 91.2 75.8 AD- FTLD- 83.3 94.7 AD-MCI- Genetically [43] OASIS kSVM-DT ALS-PCA PCA 80-- NC Features AD- NC Deep Wavelet [44] ADNI SVM AAL Sparse--- MCIc-MCInc ROI learning SVM pMCI [12] ADNI RLR Voxel based- 90.06-- LDS sMCI AD-NC ...
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. ...
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