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Titlebook: Sampling Theory, a Renaissance; Compressive Sensing G?tz E. Pfander Book 2015 Springer International Publishing Switzerland 2015 Compressi

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發(fā)表于 2025-3-21 19:28:05 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Sampling Theory, a Renaissance
副標(biāo)題Compressive Sensing
編輯G?tz E. Pfander
視頻videohttp://file.papertrans.cn/861/860753/860753.mp4
概述Tutorial style articles on new high-impact topics in sampling and applications.Offers experts in sampling theory (mathematicians and engineers) new insights into the wide area of sampling theory.Inclu
叢書(shū)名稱(chēng)Applied and Numerical Harmonic Analysis
圖書(shū)封面Titlebook: Sampling Theory, a Renaissance; Compressive Sensing G?tz E. Pfander Book 2015 Springer International Publishing Switzerland 2015 Compressi
描述.Reconstructing or approximating objects from seemingly incomplete information is a frequent challenge in mathematics, science, and engineering. A multitude of tools designed to recover hidden information are based on Shannon’s classical sampling theorem, a central pillar of Sampling Theory. The growing need to efficiently obtain precise and tailored digital representations of complex objects and phenomena requires the maturation of available tools in Sampling Theory as well as the development of complementary, novel mathematical theories. Today, research themes such as Compressed Sensing and Frame Theory re-energize the broad area of Sampling Theory. This volume illustrates the renaissance that the area of Sampling Theory is currently experiencing. It touches upon trendsetting areas such as Compressed Sensing, Finite Frames, Parametric Partial Differential Equations, Quantization, Finite Rate of Innovation, System Theory, as well as sampling in Geometry and Algebraic Topology..
出版日期Book 2015
關(guān)鍵詞Compressive Sensing; Fourier Analysis; Frame Theory; Random Measurements; Sampling Theory; Sparsity; infor
版次1
doihttps://doi.org/10.1007/978-3-319-19749-4
isbn_softcover978-3-319-79286-6
isbn_ebook978-3-319-19749-4Series ISSN 2296-5009 Series E-ISSN 2296-5017
issn_series 2296-5009
copyrightSpringer International Publishing Switzerland 2015
The information of publication is updating

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System Approximations and Generalized Measurements in Modern Sampling Theoryte integrable Fourier transform. If the samples are acquired by point evaluations of the input signal ., then there exist stable LTI systems H such that the approximation process does not converge to the desired output H. even if the oversampling factor is arbitrarily large. If one allows generalize
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How To Best Sample a Solution Manifold?wever been confined so far essentially to well-conditioned coercive problems. A critical issue is therefore an extension of these concepts to a wider range of problem classes for which the conventional methods do not work well. A second main topic of this chapter is therefore to outline recent devel
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OperA: Operator-Based Annihilation for Finite-Rate-of-Innovation Signal Samplingtial-spline construction. Monte Carlo performance analysis in the presence of noise shows that annihilation on interleaved sampling grids leads to more noise-robust estimates than annihilation on uniform sampling grids.
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Michael Robinsona neutral context? And what prevents our explaining this, at any rate partially, by reference to the effects that the stimulation of one area of the retina has on the effects in another area produced by accompanying or parallel stimulation, wherever in the nervous system the final integrating mechan
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