存货清单 发表于 2025-3-21 18:02:01

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ARCH 发表于 2025-3-21 21:50:57

The Geometry of Compressed Sensing,instead of vector data, in many problems, data is more naturally expressed in matrix form (for example a video is often best represented in a pixel by time matrix). A powerful constraint on matrices are constraints on the matrix rank. For example, in low-rank matrix recovery, the goal is to reconstr

有偏见 发表于 2025-3-22 00:46:33

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exhibit 发表于 2025-3-22 08:20:19

Nonnegative Tensor Decomposition,mension less using the so-called t-product. A demonstration on an application in facial recognition shows the potential promise of the overall approach. We discuss a number of algorithmic options for solving the resulting optimization problems, and modification of such algorithms for increasing the

培养 发表于 2025-3-22 11:03:21

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companion 发表于 2025-3-22 13:34:43

Sparse Nonlinear MIMO Filtering and Identification,acing emphasis on minimal input resources and blind identification whereby only output samples are available plus a–priori information on input characteristics. Based on this taxonomy a variety of algorithms, existing and new, are studied and evaluated by simulations.

companion 发表于 2025-3-22 18:08:06

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hypotension 发表于 2025-3-22 22:11:21

Sparsity and Compressed Sensing in Mono-Static and Multi-Static Radar Imaging,terns reflect spectral and spatial diversity trade-offs. Characterization of the expected quality of the reconstructed images in these scenarios prior to actual data collection is a problem of central interest in task planning for multi-mode radars. Compressed sensing theory argues that the mutual c

acolyte 发表于 2025-3-23 04:59:27

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ticlopidine 发表于 2025-3-23 08:58:34

Konzepte zur Erfolgs- und Risikoanalyse,d as .-regularized . regression. We show that, under standard restricted isometry property (RIP) assumptions on the design matrix, .-minimization can provide stable recovery of a sparse signal in presence of exponential-family noise, and state some sufficient conditions on the noise distribution tha
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查看完整版本: Titlebook: Compressed Sensing & Sparse Filtering; Avishy Y. Carmi,Lyudmila Mihaylova,Simon J. Godsil Book 2014 Springer-Verlag Berlin Heidelberg 2014