愤慨一下
发表于 2025-3-26 23:45:39
D. Scheidegger,A. Urwyler,M. KaufmannThis chapter illustrates standard ideas and tools that have been developed since the inception of the Compressed Sensing paradigm. It does so pairing formal statements with a driving low-dimensional example allowing graphical explanations.
Functional
发表于 2025-3-27 04:32:09
http://reply.papertrans.cn/15/1446/144551/144551_32.png
预测
发表于 2025-3-27 09:19:23
https://doi.org/10.1007/978-3-319-61373-4Compressed Sensing; Compressive Sensing; Compressed Sensing & Sparse Filtering; Compressive Sensing for
迅速成长
发表于 2025-3-27 12:13:07
http://reply.papertrans.cn/15/1446/144551/144551_34.png
骂人有污点
发表于 2025-3-27 16:56:05
Mauro Mangia,Fabio Pareschi,Gianluca SettiDiscusses the theory as necessary, but either in parallel with extremely simple examples or with reference to the performances that can be actually obtained by CS-based sensing systems.Describes a des
培养
发表于 2025-3-27 21:25:20
http://reply.papertrans.cn/15/1446/144551/144551_36.png
Watemelon
发表于 2025-3-27 23:03:35
http://reply.papertrans.cn/15/1446/144551/144551_37.png
赞美者
发表于 2025-3-28 02:06:57
Georg Heberer,Wolfgang Köle,Harald Tschernetion systems based on CS. This is done by quantifying and exploiting the anisotropy in the energy distribution of real-world signal with a mechanism entailing a minimum if not negligible increase in the complexity of the acquisition operations. In fact, the mechanism is not adaptive in real-time but
evanescent
发表于 2025-3-28 08:32:50
Georg Heberer,Wolfgang Köle,Harald Tscherneore sophisticated optimization tools are developed. The overall algorithmic complexity of the acquisition procedure is also considered and a knob controlling it is introduced. This further degree of freedom is shown to allow the administration of the trade-off between acquisition complexity and the
陈列
发表于 2025-3-28 11:17:26
https://doi.org/10.1007/978-3-642-20475-3realization. A generator of random vectors whose entries have only few possible values (say 0 and 1, or − 1 and 1, or − 1, 0, and 1) and whose second-order statistics (i.e., correlation or power spectrum) are as close as possible to some given specification. The constraints on the values make this p