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For math proofs... Simple template so I don't have to copy and paste all the time!

The output of this table is used as Table 1 of the paper: Wangyan Li, Zidong Wang, Guoliang Wei, Lifeng Ma, Jun Hu, and Derui Ding, “A Survey on Multisensor Fusion and Consensus Filtering for Sensor Networks,” Discrete Dynamics in Nature and Society, vol. 2015, Article ID 683701, 12 pages, 2015. doi: 10.1155/2015/683701.

HoTT

Compressive Sensing is a Signal Processing technique, which gave a break through in 2004. The main idea of CS is, by exploiting the sparsity nature of the signal (in any domain), we can reconstruct the signal from very fewer samples than required by Shannon-Nyquist sampling theorem. Reconstructing a sparse signal from fewer samples is equivalent to solving a under-determined system with sparsity constraints. Least square solution to such a problem yield poor `results because sparse signals cannot be well approximated to a least norm solution. Instead we use l1 norm(convex) to solve this problem which is the best approximation to the exact solution given by l0 norm(non-convex). In this paper we plan to discuss three applications of CS in estimation theory. They are, CS based reliable Channel estimation assuming sparsity in the channel is known for TDS-OFDM systems[1]. Indoor location estimation from received signal strength (RSS) where CS is used to reconstruct the radio map from RSS measurements[2]. Identifying that subspace in which the signal of interest lies using ML estimation, assuming signal lies in a union of subspaces which is a standard sparsity assumption according to CS theory[3]. Index terms : Compressive Sensing, Indoor positioning, fingerprinting, radio map, Maximum likelihood estimation, union of linear subspaces, subspace recovery.

Cálculo de momento de inercia de un cilindro solido y una esfera hueca

This is a skeleton file demonstrating the use of IEEEtran.cls with an IEEE journal paper. To start writing your manuscript in Overleaf, simply click the 'Open as template' button above. Additional IEEE templates are also available - please use the tags below to view. These include: additional article templates for specific journals (e.g. IEEE Photonics), templates for conference papers, and user-submitted examples and adaptations.

This is a skeleton file demonstrating the use of IEEEtran.cls (requires IEEEtran.cls version 1.8b or later) with an IEEE Computer Society conference paper. For other IEEE conferences, please see the IEEE conference paper template, and to find additional IEEE templates please use the tags below. IEEEtran.cls version: 1.8b

This is a skeleton template file demonstrating the use of IEEEtran.cls with an IEEE Transactions on Magnetics journal paper. IEEEtran.cls version: 1.8b

This demo file is intended to serve as a ``starter file'' for IEEE conference papers produced under LaTeX using IEEEtran.cls version 1.8b and later. This is one of a number of templates using the IEEE style that are available on Overleaf to help you get started - use the tags below to find more. IEEEtran.cls version: 1.8b