38,024 research outputs found

    Wavelets and graph CC^*-algebras

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    Here we give an overview on the connection between wavelet theory and representation theory for graph CC^{\ast}-algebras, including the higher-rank graph CC^*-algebras of A. Kumjian and D. Pask. Many authors have studied different aspects of this connection over the last 20 years, and we begin this paper with a survey of the known results. We then discuss several new ways to generalize these results and obtain wavelets associated to representations of higher-rank graphs. In \cite{FGKP}, we introduced the "cubical wavelets" associated to a higher-rank graph. Here, we generalize this construction to build wavelets of arbitrary shapes. We also present a different but related construction of wavelets associated to a higher-rank graph, which we anticipate will have applications to traffic analysis on networks. Finally, we generalize the spectral graph wavelets of \cite{hammond} to higher-rank graphs, giving a third family of wavelets associated to higher-rank graphs

    Orthogonal Wavelets via Filter Banks: Theory and Applications

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    Wavelets are used in many applications, including image processing, signal analysis and seismology. The critical problem is the representation of a signal using a small number of computable functions, such that it is represented in a concise and computationally efficient form. It is shown that wavelets are closely related to filter banks (sub band filtering) and that there is a direct analogy between multiresolution analysis in continuous time and a filter bank in discrete time. This provides a clear physical interpretation of the approximation and detail spaces of multiresolution analysis in terms of the frequency bands of a signal. Only orthogonal wavelets, which are derived from orthogonal filter banks, are discussed. Several examples and applications are considered

    Approximation Theory XV: San Antonio 2016

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    These proceedings are based on papers presented at the international conference Approximation Theory XV, which was held May 22\u201325, 2016 in San Antonio, Texas. The conference was the fifteenth in a series of meetings in Approximation Theory held at various locations in the United States, and was attended by 146 participants. The book contains longer survey papers by some of the invited speakers covering topics such as compressive sensing, isogeometric analysis, and scaling limits of polynomials and entire functions of exponential type. The book also includes papers on a variety of current topics in Approximation Theory drawn from areas such as advances in kernel approximation with applications, approximation theory and algebraic geometry, multivariate splines for applications, practical function approximation, approximation of PDEs, wavelets and framelets with applications, approximation theory in signal processing, compressive sensing, rational interpolation, spline approximation in isogeometric analysis, approximation of fractional differential equations, numerical integration formulas, and trigonometric polynomial approximation

    Data expansion with Huffman codes

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    The following topics were dealt with: Shannon theory; universal lossless source coding; CDMA; turbo codes; broadband networks and protocols; signal processing and coding; coded modulation; information theory and applications; universal lossy source coding; algebraic geometry codes; modelling analysis and stability in networks; trellis structures and trellis decoding; channel capacity; recording channels; fading channels; convolutional codes; neural networks and learning; estimation; Gaussian channels; rate distortion theory; constrained channels; 2D channel coding; nonparametric estimation and classification; data compression; synchronisation and interference in communication systems; cyclic codes; signal detection; group codes; multiuser systems; entropy and noiseless source coding; dispersive channels and equalisation; block codes; cryptography; image processing; quantisation; random processes; wavelets; sequences for synchronisation; iterative decoding; optical communications
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