"Haar wavelet"의 두 판 사이의 차이

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* ID :  [https://www.wikidata.org/wiki/Q766198 Q766198]
 
* ID :  [https://www.wikidata.org/wiki/Q766198 Q766198]
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* [{'LOWER': 'haar'}, {'LEMMA': 'wavelet'}]

2021년 2월 17일 (수) 00:48 기준 최신판

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말뭉치

  1. Later the operational matrix which is obtained from Haar wavelet is used to find the numerical solutions of some differential equations.[1]
  2. Calculating the multi-resolution Haar wavelet transform and inverse.[2]
  3. The aim of this paper is to analyse the capabilities of Haar wavelet power spectrum in selecting informative features in microarray data on the basis of the inherent properties captured by them.[3]
  4. In this paper, we analyse the capability of wavelet power spectrum in feature selection and we propose a method of feature selection based on Haar wavelet power spectrum.[3]
  5. The method is a model independent approach, a filter feature selection method, based on the Haar wavelet power spectrum of the microarray data.[3]
  6. It can be easily examined that both the low pass and high pass filters of Haar wavelet are quadratic in nature using the discussion presented in the previous paragraph.[3]
  7. We note, for instance, that the Haar wavelet does map successively into the smoothness classes M n , like the LULU smoothers, but skips progressively more of them.[4]
  8. In mathematics, the Haar wavelet is a sequence of rescaled "square-shaped" functions which together form a wavelet family or basis.[5]
  9. We have developed a new numerical method based on Haar wavelet (HW) in this article for the numerical solution (NS) of one‐ and two‐dimensional hyperbolic Telegraph equations (HTEs).[6]
  10. In this work, we explore the Haar wavelet to model the space-frequency localization property of human visual system (HVS).[7]
  11. Haar wavelet functions have been used since year at 1910.[8]
  12. We present a high-speed single pixel flow imager based on an all-optical Haar wavelet transform of moving objects.[9]
  13. Here we present a high-speed BS imaging system based on an all-optical Haar wavelet transform.[9]
  14. Here we implement an all-optical Haar wavelet transform for image acquisition and compression.[9]
  15. We have demonstrated an all-optical Haar wavelet transform engine that takes advantage of ultra-high speed chirped pulse patterning in order to create structured illumination.[9]
  16. the Fast Haar Wavelet Transform (FHWT) algorithm applied to satellite-images fusion.[10]
  17. The present paper focuses on implementing the fast Haar wavelet transform (FHWT) for the fusion of satellite images.[10]
  18. The second stage dealt with the implementation of the Fast Haar Wavelet Transform FHWT, which is the main focus of this study.[10]
  19. The proposed method consists of an optimized Haar wavelet transformation (HWT).[11]
  20. This high PSNR value of Haar wavelet represents that the Haar wavelet transform is applicable to reconstruct the original image with no loss of original information in the image.[11]
  21. Features are calculated using Haar wavelet transform and principle component analysis based on the contrast equalization of brain slices.[11]
  22. Especially, the Haar wavelet transform efficiently allows analyzing the image on spectral domain.[11]
  23. Figures 3 and 4 show the row decomposition and the column decomposition using Haar wavelet, respectively.[12]
  24. In order to simplify computational complexity, a novel JND model based on Haar wavelet is proposed as follows.[12]
  25. For computing the Haar wavelet transform, however, we can do better.[13]
  26. Since the normalized Haar filter bank is orthogonal, this fact implies that the corresponding normalized Haar wavelet basis is orthonormal.[13]
  27. Numerical solution of a class of delay differential and delay partial differential equations via Haar wavelet.[14]
  28. A new method based on Haar wavelet for the numerical solution of two-dimensional nonlinear integral equations.[14]
  29. Haar wavelet method for solving lumped and distributed-parameter systems.[14]
  30. Haar wavelet method for solving fishers equation.[14]
  31. In this paper, numerical solutions of Riccati and fractional Riccati differential equations are obtained by the Haar wavelet collocation method.[15]
  32. An operational matrix of integration based on the Haar wavelet is established, and the procedure for applying the matrix to solve these equations.[15]
  33. The fundamental idea of Haar wavelet method is to convert the proposed differential equations into a group of non-linear algebraic equations.[15]
  34. Haar wavelet is a sequence of rescaled square-shaped functions which together form a wavelet family or basis.[16]
  35. The principle and its derivation of the Haar wavelet method for Hankel transforms were put forward.[17]
  36. Numerical examples and engineering application showed that the precision of Haar wavelet method is about magnitude of and ; it can maintain good accuracy when using fewer wavelet coefficients.[17]
  37. Hence, the simplest and orthogonal Haar wavelet is adopted.[17]
  38. Firstly, the principle of Haar wavelet decomposition is presented and the HT algorithm based on wavelet is given.[17]
  39. we will present a new approach to solve certain classes of linear or nonlinear boundary value problems of generalized fractional differential equations numerically, called Green–Haar wavelet method.[18]
  40. Here we derive an inequality in the context of an upper bound for the Caputo–Katugampola fractional differential operator which shows the convergence of the Haar wavelet technique.[18]

소스

  1. ↑ Haar Wavelet: History and Its Applications
  2. ↑ Lecture 12 - Haar wavelet example
  3. ↑ 3.0 3.1 3.2 3.3 Feature selection using Haar wavelet power spectrum
  4. ↑ Haar Wavelet - an overview
  5. ↑ Haar wavelet
  6. ↑ A Haar wavelet collocation approach for solving one and two‐dimensional second‐order linear and nonlinear hyperbolic telegraph equations
  7. ↑ Image quality measurement using the Haar wavelet
  8. ↑ (PDF) Haar Wavelet Method to Spectral Analysis Continuous Wavelet Transform 1D Using Whistle Sound to Position of Dolphins (Tursiops aduncus)
  9. ↑ 9.0 9.1 9.2 9.3 High-speed all-optical Haar wavelet transform for real-time image compression
  10. ↑ 10.0 10.1 10.2 Implementing Fast-Haar Wavelet transform on original Ikonos images to perform image fusion: qualitative assessment
  11. ↑ 11.0 11.1 11.2 11.3 An efficient JPEG image compression based on Haar wavelet transform, discrete cosine transform, and run length encoding techniques for advanced manufacturing processes
  12. ↑ 12.0 12.1 Haar-Wavelet-Based Just Noticeable Distortion Model for Transparent Watermark
  13. ↑ 13.0 13.1 Introduction to Wavelets II
  14. ↑ 14.0 14.1 14.2 14.3 Application of higher order Haar wavelet method for solving nonlinear evolution equations
  15. ↑ 15.0 15.1 15.2 Haar Wavelet Collocation Method for Solving Riccati and Fractional Riccati Differential Equations
  16. ↑ EEG Signal Denoising Using Haar Transform and Maximal Overlap Discrete Wavelet Transform (MODWT) for the Finding of Epilepsy
  17. ↑ 17.0 17.1 17.2 17.3 A Stable Hankel Transforms Algorithm Based on Haar Wavelet Decomposition for Noisy Data
  18. ↑ 18.0 18.1 Green–Haar wavelets method for generalized fractional differential equations

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