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Автор: Grafiati
Опубліковано: 11 вересня 2023

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Статті в журналах з теми "MULTIWAVELET"

1

Shouzhi, Yang. "Biorthogonal interpolatory multiscaling functions and corresponding multiwavelets." ANZIAM Journal 49, no. 1 (July 2007): 85–97. http://dx.doi.org/10.1017/s1446181100012694.

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A method for constructing a pair of biorthogonal interpolatory multiscaling functions is given and an explicit formula for constructing the corresponding biorthogonal multiwavelets is obtained. A multiwavelet sampling theorem is also established. In addition, we improve the stability of the biorthogonal interpolatory multiwavelet frame by the linear combination of a pair of biorthogonal interpolatory multiwavelets. Finally, we give an example illustrating how to use our method to construct biorthogonal interpolatory multiscaling functions and corresponding multiwavelets.
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2

Huang, Yongdong, Qiufu Li, and Ming Li. "Minimum-Energy Multiwavelet Frames with Arbitrary Integer Dilation Factor." Mathematical Problems in Engineering 2012 (2012): 1–37. http://dx.doi.org/10.1155/2012/640789.

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In order to organically combine the minimum-energy frame with the significant properties of multiwavelets, minimum-energy multiwavelet frames with arbitrary integer dilation factor are studied. Firstly, we define the concept of minimum-energy multiwavelet frame with arbitrary dilation factor and present its equivalent characterizations. Secondly, some necessary conditions and sufficient conditions for minimum-energy multiwavelet frame are given. Thirdly, the decomposition and reconstruction formulas of minimum-energy multiwavelet frame with arbitrary integer dilation factor are deduced. Finally, we give several numerical examples based on B-spline functions.
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3

Taha, Saleem, and Walid Mahmood. "New techniques for Daubechies wavelets and multiwavelets implementation using quantum computing." Facta universitatis - series: Electronics and Energetics 26, no. 2 (2013): 145–56. http://dx.doi.org/10.2298/fuee1302145t.

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In this paper, new techniques to implement the Daubechies wavelets and multiwavelets are presented using quantum computing synthesis structures. Also, a new quantum implementation of inverse Daubechies multiwavelet transform is proposed. The permutation matrices, particular unitary matrices, play a pivotal role. The particular set of permutation matrices arising in quantum wavelet and multiwavelet transforms is considered, and efficient quantum circuits that implement them are developed. This allows the design of efficient and complete quantum circuits for the quantum wavelet and multiwavelet transforms.
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4

NGUYEN, PHAN. "BIORTHOGONAL MULTIWAVELETS RELATED BY DIFFERENTIATION." International Journal of Wavelets, Multiresolution and Information Processing 12, no. 02 (March 2014): 1450021. http://dx.doi.org/10.1142/s0219691314500210.

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We provide a procedure for constructing biorthogonal multiwavelets from a family of biorthogonal multiscaling functions compactly supported on [-1,1]. The scaling vectors and the associated multiwavelets are piecewise continuously differentiable, symmetrical and possess approximation order three. The construction of scaling vectors is accomplished using quadratic fractal interpolation functions. The filters corresponding to scaling vectors possess certain properties which enable us to construct a new pair of biorthogonal scaling vectors and associated multiwavelets with different regularity and approximation order, related to the old ones by differentiation. The old and new biorthogonal multiwavelet systems give rise to compactly supported biorthogonal multiwavelet basis for the space of divergence-free vector fields on the upper half plane with the Navier boundary condition.
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5

Mahmoud, Waleed Ameen, Ali Ibrahim Abbas, and Nuha Abdul Sahib Alwan. "FACE IDENTIFICATION USING BACK-PROPAGATION ADAPTIVE MULTIWAVENET." Journal of Engineering 18, no. 03 (July 21, 2023): 392–402. http://dx.doi.org/10.31026/j.eng.2012.03.12.

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Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a recognition rate of 97.75% in the presence of facial expression, lighting and pose variations. Results are compared with its wavelet-based counterpart where it obtained a recognition rate of 10.4%. The proposed multiwavenet demonstrated very good recognition rate in the presence of variations in facial expression, lighting and pose and outperformed its wavelet-based counterpart.
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6

Saini, Manish Kumar, and Rajiv Kapoor. "Power Quality Events Classification Using MWT and MLP." Advanced Materials Research 403-408 (November 2011): 4266–71. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.4266.

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The work presented uses multiwavelet because of its inherent property to resolve the signal better than all single wavelets. Multiwavelets are based on more than one scaling function. The proposed methodology utilizes an enhanced resolving capability of multiwavelet to recognize power system disturbances. The disturbance classification schema is performed with multiwavelet neural network (MWNN). It performs a feature extraction and a classification algorithm composed of a multiwavelet feature extractor based on norm entropy and a classifier based on a multi-layer perceptron. The performance of this classifier is evaluated by using total 1000 PQ disturbance signals which are generated the based model. The classification performance of different PQ disturbance using proposed algorithm is tested. The rate of average correct classification is about 99.65% for the different PQ disturbance signals and noisy disturbances.
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7

BACCHELLI, SILVIA, and SERENA PAPI. "A NOTE ON A MATRIX APPROACH TO MULTIWAVELET APPLICATIONS." International Journal of Wavelets, Multiresolution and Information Processing 04, no. 03 (September 2006): 509–22. http://dx.doi.org/10.1142/s0219691306001415.

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Анотація:
In recent years, many papers have been devoted to the topic of balanced multiwavelets, namely, multiwavelet bases which are especially designed to avoid the prefiltering step in the implementation of the multiwavelet transform. In this work, we give a simple algebraic proof of how scalar wavelets can be reinterpreted as the most natural balanced multiwavelets, which maintain the good properties of the wavelet bases they come from. We then show how these new bases can be successfully used to apply matrix thresholding for the denoising of images corrupted by Gaussian noise. In fact, this new approach discovers a balanced matrix nature in Daubechies bases, hence obtaining better numerical results with respect to those achieved via scalar thresholding. In particular, this reinterpretation of scalar wavelets as balanced multiwavelets allows us to successfully use the thresholding filters, previously introduced in the scalar case, in a matrix setting.
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8

Lang, W. Christopher. "Fractal multiwavelets related to the cantor dyadic group." International Journal of Mathematics and Mathematical Sciences 21, no. 2 (1998): 307–14. http://dx.doi.org/10.1155/s0161171298000428.

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Orthogonal wavelets on the Cantor dyadic group are identified with multiwavelets on the real line consisting of piecewise fractal functions. A tree algorithm for analysis using these wavelets is described. Multiwavelet systems with algorithms of similar structure include certain orthogonal compactly supported multiwavelets in the linear double-knot spline spaceS1,2.
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9

Hnativ, Lev. "Orthonormalized basic of fractal stepped multiwavelets – a new multiwavelet technology for signal and image processing." Physico-mathematical modelling and informational technologies, no. 32 (July 7, 2021): 91–95. http://dx.doi.org/10.15407/fmmit2021.32.091.

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A new class of fractal step functions with linear and nonlinear changes in values is described, and on their basis a recurrent method for constructing functions of a new class of fractal step multiwavelets (FSMW) of various shapes with linear and nonlinear changes in values is developed. A method and an algorithm for constructing a whole family of basic FSMW systems have been developed. An algorithm for calculating the coefficients of a discrete multiwavelet transform based on a multiwavelet packet without performing convolution and decimated sampling operations, in contrast to the classical method, is presented. A method and algorithm for fast multiwavelet transform of low computational complexity has been developed, which, in comparison with the well-known classical Mall's algorithm, is 70 times less in multiplicative complexity, and 20 times less in additive complexity.
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10

Saini, Manish Kumar, Rajiv Kapoor, and Bharat Bhushan Sharma. "PQ Event Classification Using Fuzzy Classifier." Advanced Materials Research 403-408 (November 2011): 3854–58. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.3854.

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Анотація:
The work presented here uses multiwavelet because of its inherent property to resolve the signal better than all single wavelets. Multiwavelets are based on more than one scaling function. The proposed methodology utilizes an enhanced resolving capability of multiwavelet to recognize power quality events. PQ events classification scheme is performed using multiwavelet transform for feature extraction and fuzzy classifier for classification. In proposed algorithm,statistical features (.i.e. mean, standard deviation, variation etc.) and energy of the signal at different decomposition levels have been considered as feature vectors. The performance of fuzzy classifier has been evaluated by using total 1000 PQ disturbance signals which are generated using the based model. The classification performance of different PQ events using proposed algorithm has been tested. The rate of average correct classification is about 99.95% for the different PQ disturbance signals and noisy disturbances.
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Дисертації з теми "MULTIWAVELET"

1

Koch, Karsten. "Interpolating scaling vectors and multiwavelets in Rd : a multiwavelet cookery book /." Berlin : Logos-Verl, 2007. http://deposit.d-nb.de/cgi-bin/dokserv?id=2917176&prov=M&dok_var=1&dok_ext=htm.

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Koch, Karsten. "Interpolating scaling vectors and multiwavelets in Rd a multiwavelet cookery book." Berlin Logos-Verl, 2006. http://deposit.d-nb.de/cgi-bin/dokserv?id=2917176&prov=M&dok_var=1&dok_ext=htm.

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3

Brodin, Andreas. "Multiwavelet analysis on fractals." Doctoral thesis, Umeå : Dept. of Mathematics and Mathematical Statistics, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-1131.

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4

Martin, Michael B. "Applications of Multiwavelets to Image Compression." Thesis, Virginia Tech, 1999. http://hdl.handle.net/10919/33601.

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Methods for digital image compression have been the subject of much study over the past decade. Advances in wavelet transforms and quantization methods have produced algorithms capable of surpassing the existing image compression standards like the Joint Photographic Experts Group (JPEG) algorithm. For best performance in image compression, wavelet transforms require filters that combine a number of desirable properties, such as orthogonality and symmetry. However, the design possibilities for wavelets are limited because they cannot simultaneously possess all of these desirable properties. The relatively new field of multiwavelets shows promise in removing some of the limitations of wavelets. Multiwavelets offer more design options and hence can combine all desirable transform features. The few previously published results of multiwavelet-based image compression have mostly fallen short of the performance enjoyed by the current wavelet algorithms. This thesis presents new multiwavelet transform methods and measurements that verify the potential benefits of multiwavelets. Using a zerotree quantization scheme modified to better match the unique decomposition properties of multiwavelets, it is shown that the latest multiwavelet filters can give performance equal to, or in many cases superior to, the current wavelet filters. The performance of multiwavelet packets is also explored for the first time and is shown to be competitive to that of wavelet packets in some cases. The wavelet and multiwavelet filter banks are tested on a much wider range of images than in the usual literature, providing a better analysis of the benefits and drawbacks of each. NOTE: (03/2007) An updated copy of this ETD was added after there were patron reports of problems with the file.
Master of Science
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5

Garcia, Bautista Javier. "Multiwavelet-based hp-adaptation for discontinuous Galerkin methods." Thesis, Ecole centrale de Nantes, 2022. http://www.theses.fr/2022ECDN0046.

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L’objectif principal de cette thèse est de développer une méthode hp-adaptative efficace en termes de coût et précision pour les schémas Galerkin discontinus appliqués aux équations de Navier-Stokes, en combinant flexibilité de l’adaptation a posteriori et précision de l’adaptation multi-résolution. Les performances de l’algorithme d’adaptation hp sont illustrées sur plusieurs cas d’écoulements stationnaires en une et deux dimensions. La première direction de recherche emploie une nouvelle méthodologie basée sur les multiondelettes pour estimer l’erreur de discrétisation de la solution numérique dans le contexte de simulations avec adaptation h. Les résultats démontrent clairement la viabilité de cette méthode pour atteindre un gain de calcul significatif par rapport àun raffinement de maillage uniforme. La deuxième voie de recherche aborde l’analyse et le développement d’une nouvelle stratégied’adaptation hp basée sur la décroissance du spectre des multi-ondelettes comme critère adaptation hp. Cette stratégie permet de discriminer avec succès les régions caractérisées par une grande régularité de celles contenant des phénomènes discontinus. De manière remarquable, l’algorithme d’adaptation hp est capable d’atteindre une haute précision caractéristique des solutions numériques d’ordre élevé tout en évitant les oscillations indésirables en adoptant des approximations d’ordre réduit à proximité des singularités
The main objective of the present thesis is to devise, construct and validate computationally efficient hp-adaptive discontinuous Galerkin schemes of the Navier-Stokes equations by bringing together the flexibility of a posteriori error driven adaptation and the accuracy of multiresolution-based adaptation. The performance of the hp-algorithm is illustrated by several steady flows in one and two dimensions.The first research direction employs a new multiwavelet-based methodology to estimate the discretization error of the numerical solution in the context of h-adaptive simulations. The results certainly demonstrate the viability of h-refinement to reach a significant computational gain with respect to uniformly refined grids. The second line of investigation addresses the analysis and development of a new hp-adaptive strategy based on the decay of the multiwavelet spectrum to drive hp-adaptive simulations. The strategy successfully discriminates between regions characterized by high regularity and discontinuous phenomena and their vicinity. Remarkably, the developed hp-adaptation algorithm is able to achieve the high accuracy characteristic of high-order numerical solutions while avoiding unwanted oscillations by adopting low-order approximations in the proximity of singularities
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6

Fann, George I.-Pan. "Efficient multiwavelet representation of the projector on divergence-free functions." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/9176.

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7

Castrillón, Candás Julio E. (Julio Enrique). "Spatially adaptive multiwavelet representations on unstructured grids with applications to multidimensional computational modeling." Thesis, Massachusetts Institute of Technology, 2001. http://hdl.handle.net/1721.1/8923.

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Анотація:
Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2001.
Includes bibliographical references (p. 130-134).
In this thesis, we develop wavelet surface wavelet representations for complex surfaces, with the goal of demonstrating their potential for 3D scientific and engineering computing applications. Surface wavelets were originally developed for representing geometric objects in a multiresolution format in computer graphics. However, we further extend the construction of surface wavelets and prove the existence of a large class of multiwavelets in Rn with vanishing moments around corners that are well suited for complex geometries. These wavelets share all of the major advantages of conventional wavelets, in that they provide an analysis tool for studying data, functions and operators at different scales. However, unlike conventional wavelets, which are restricted to uniform grids, surface wavelets have the power to perform signal processing operations on complex meshes, such as those encountered in finite element modeling. This motivates the study of surface wavelets as an efficient representation for the modeling and simulation of physical processes. We show how surface wavelets can be applied to partial differential equations, cast in the integral form. We analyze and implement the wavelet approach for a model 3D potential problem using a surface wavelet basis with linear interpolating properties.
(cont.) We show both theoretically and experimentally that an O(h2/n) convergence rate, hn being the mesh size, can be obtained by retaining only O((logN)7/2 N) entries in the discrete operator matrix, where N is the number of unknowns. Moreover our theoretical proof of accuracy vs compression is applicable to a large class of Calderón-Zygmund integral operators. In principle, this convergence analysis may be extended to higher order wavelets with greater vanishing moment. This results in higher convergence and greater compression.
by Julio E. Castrillón Candás.
Ph.D.
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8

Jacobs, Denise Anne. "Multiwavelets in higher dimensions." Diss., Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/28780.

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9

Strela, Vasily. "Multiwavelets--theory and applications." Thesis, Massachusetts Institute of Technology, 1996. http://hdl.handle.net/1721.1/10631.

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10

Iyer, Lakshmi Ramachandran. "Image Compression Using Balanced Multiwavelets." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/33748.

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The success of any transform coding technique depends on how well the basis functions represent the signal features. The discrete wavelet transform (DWT) performs a multiresolution analysis of a signal; this enables an efficient representation of smooth and detailed signal regions. Furthermore, computationally efficient algorithms exist for computing the DWT. For these reasons, recent image compression standards such as JPEG2000 use the wavelet transform. It is well known that orthogonality and symmetry are desirable transform properties in image compression applications. It is also known that the scalar wavelet transform does not possess both properties simultaneously. Multiwavelets overcome this limitation; the multiwavelet transform allows orthogonality and symmetry to co-exist. However recently reported image compression results indicate that the scalar wavelets still outperform the multiwavelets in terms of peak signal-to-noise ratio (PSNR). In a multiwavelet transform, the balancing order of the multiwavelet is indicative of its energy compaction efficiency (usually a higher balancing order implies lower mean-squared-error, MSE, in the compressed image). But a high balancing order alone does not ensure good image compression performance. Filter bank characteristics such as shift-variance, magnitude response, symmetry and phase response are important factors that also influence the MSE and perceived image quality. This thesis analyzes the impact of these multiwavelet characteristics on image compression performance. Our analysis allows us to explain---for the first time---reasons for the small performance gap between the scalar wavelets and multiwavelets. We study the characteristics of five balanced multiwavelets (and 2 unbalanced multiwavelets) and compare their image compression performance for grayscale images with the popular (9,7)-tap and (22,14)-tap biorthogonal scalar wavelets. We use the well-known SPIHT quantizer in our compression scheme and utilize PSNR and subjective quality measures to assess performance. We also study the effect of incorporating a human visual system (HVS)-based transform model in our multiwavelet compression scheme. Our results indicate those multiwavelet properties that are most important to image compression. Moreover, the PSNR and subjective quality results depict similar performance for the best scalar wavelets and multiwavelets. Our analysis also shows that the HVS-based multiwavelet transform coder considerably improves perceived image quality at low bit rates.
Master of Science
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Книги з теми "MULTIWAVELET"

1

Wavelets and multiwavelets. Boca Raton, FL: Chapman & Hall/CRC Press, 2004.

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2

Aldroubi, Akram, and EnBing Lin, eds. Wavelets, Multiwavelets, and Their Applications. Providence, Rhode Island: American Mathematical Society, 1998. http://dx.doi.org/10.1090/conm/216.

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3

Akram, Aldroubi, and Lin EnBing 1953-, eds. Wavelets, multiwavelets, and their applications: AMS Special Session on Wavelets, Multiwavelets, and Their Applications, January, 1997, San Diego, California. Providence, R.I: American Mathematical Society, 1998.

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4

Keinert, Fritz. Wavelets and Multiwavelets. Taylor & Francis Group, 2003.

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5

Keinert, Fritz. Wavelets and Multiwavelets. Taylor & Francis Group, 2003.

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6

Keinert, Fritz. Wavelets and Multiwavelets. Taylor & Francis Group, 2003.

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7

Keinert, Fritz. Wavelets and Multiwavelets. Taylor & Francis Group, 2003.

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8

Keinert, Fritz. Wavelets and Multiwavelets. Taylor & Francis Group, 2003.

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9

Keinert, Fritz. Wavelets and Multiwavelets. Taylor & Francis Group, 2003.

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10

Keinert, Fritz. Wavelets and Multiwavelets (Studies in Advanced Mathematics). Chapman & Hall/CRC, 2003.

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Частини книг з теми "MULTIWAVELET"

1

Aldroubi, Akram. "Oblique Multiwavelet Bases." In Wavelet Theory and Harmonic Analysis in Applied Sciences, 73–91. Boston, MA: Birkhäuser Boston, 1997. http://dx.doi.org/10.1007/978-1-4612-2010-7_4.

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2

Averbuch, Amir Z., Pekka Neittaanmäki, and Valery A. Zheludev. "Multiwavelet Frames Originated From Hermite Splines." In Spline and Spline Wavelet Methods with Applications to Signal and Image Processing, 393–407. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22303-2_16.

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3

Harrison, Robert J., George I. Fann, Takeshi Yanai, and Gregory Beylkin. "Multiresolution Quantum Chemistry in Multiwavelet Bases." In Lecture Notes in Computer Science, 103–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-44864-0_11.

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4

Ashino, Ryuichi, Takeshi Mandai, and Akira Morimoto. "Continuous Multiwavelet Transform for Blind Signal Separation." In Trends in Mathematics, 219–39. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-47512-7_12.

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Kestler, S. "A Special Multiwavelet Basis for Unbounded Product Domains." In Numerical Mathematics and Advanced Applications 2011, 183–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33134-3_20.

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Sumesh, Eratt P., and Elizabeth Elias. "Optimization of Finite Difference Method with Multiwavelet Bases." In Communications in Computer and Information Science, 37–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03547-0_5.

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Fang, Zhijun, Guihua Luo, Jucheng Yang, and Shouyuan Yang. "Multiwavelet Video Coding Based on DCT Time Domain Filtering." In Transactions on Edutainment VII, 222–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-29050-3_21.

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Kim, Wonkoo, and Ching-Chung Li. "A Study on Preconditioning Multiwavelet Systems for Image Compression." In Wavelet Analysis and Its Applications, 22–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/3-540-45333-4_6.

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Jallouli, Malika, Wafa Belhadj Khalifa, Anouar Ben Mabrouk, and Mohamed Ali Mahjoub. "Toward Multiwavelet Haar-Schauder Entropy for Biomedical Signal Reconstruction." In Computer Analysis of Images and Patterns, 298–307. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-89128-2_29.

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Sankar, M. Ravi, P. Srinivas, V. Praveena, D. Bhavani, M. Sri Uma Suseela, Y. Srinivas, and Ch Venkateswara Rao. "Performance Evaluation of Multiwavelet Transform for Single Image Dehazing." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 125–33. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-28975-0_10.

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Тези доповідей конференцій з теми "MULTIWAVELET"

1

Xia, Xiang-Gen, Jeffrey S. Geronimo, Douglas P. Hardin, and Bruce W. Suter. "Computations of multiwavelet transforms." In SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, edited by Andrew F. Laine and Michael A. Unser. SPIE, 1995. http://dx.doi.org/10.1117/12.217578.

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2

Aldroubi, Akram. "Oblique multiwavelet bases: examples." In SPIE's 1996 International Symposium on Optical Science, Engineering, and Instrumentation, edited by Michael A. Unser, Akram Aldroubi, and Andrew F. Laine. SPIE, 1996. http://dx.doi.org/10.1117/12.255271.

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3

Kromka, Jozef, Ondrej Kovac, and Jan Saliga. "Multiwavelet toolbox for MATLAB." In 2022 32nd International Conference Radioelektronika (RADIOELEKTRONIKA). IEEE, 2022. http://dx.doi.org/10.1109/radioelektronika54537.2022.9764952.

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4

Ho, C. Y. F., B. W. K. Ling, and P. K. S. Tam. "Denoising by multiwavelet singularity detection." In Proceedings of 2003 International Conference on Neural Networks and Signal Processing. IEEE, 2003. http://dx.doi.org/10.1109/icnnsp.2003.1279349.

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5

Wang, Ling, and Xiang Feng. "Prefiltering of Multiwavelet with Banlancing." In 2006 International Conference on Machine Learning and Cybernetics. IEEE, 2006. http://dx.doi.org/10.1109/icmlc.2006.258874.

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6

XIA, MING-GE, YOU HE, FENG SU, and WEN OUYANG. "IMAGE FUSION USING MULTIWAVELET TRANSFORMS." In Proceedings of the International Computer Congress 2004. World Scientific Publishing Company, 2004. http://dx.doi.org/10.1142/9789812702654_0052.

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Wang, Ning, Baobin Li, and Lizhong Peng. "Multiple Description Multiwavelet Based Image Coding." In 2010 Seventh International Conference on Information Technology: New Generations. IEEE, 2010. http://dx.doi.org/10.1109/itng.2010.133.

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Peeters, R. L. M., J. M. H. Karel, R. L. Westra, S. A. P. Haddad, and W. A. Serdijn. "Multiwavelet Design for Cardiac Signal Processing." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.259733.

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Peeters, R. L. M., J. M. H. Karel, R. L. Westra, S. A. P. Haddad, and W. A. Serdijn. "Multiwavelet Design for Cardiac Signal Processing." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.4397744.

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10

Ruedin, Ana M. C. "A nonseparable multiwavelet for edge detection." In Optical Science and Technology, SPIE's 48th Annual Meeting, edited by Michael A. Unser, Akram Aldroubi, and Andrew F. Laine. SPIE, 2003. http://dx.doi.org/10.1117/12.506548.

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Звіти організацій з теми "MULTIWAVELET"

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Poppeliers, Christian. The use of multiwavelets for uncertainty estimation in seismic surface wave dispersion. Office of Scientific and Technical Information (OSTI), December 2017. http://dx.doi.org/10.2172/1413439.

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