Costa, M.H.M.: Writing on dirty paper. IEEE Transactions on Information Theory 29 (1983) 439--441 Home/Search Document Not in Database Summary Related Articles Check |
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Semidefinite Representations for Finite Varieties - Laurent (2003) (Correct)
....13, or by using their (elementary) combinatorial analogues provided by Theorems 8 and 22. We mention a result of the same flavour for the maximum stable set problem. The theta number #(G) is a well known upper bound on the stability number of a graph G = 1, n , E) introduced by Lovasz [14]; it can be obtained as optimum value of the semidefinite program: y i s.t. M 0, y ij = 0 (ij E) y 0 = 1. 11) If we impose that M (y) has rank 1 in (11) then the program solves the maximum stable set problem exactly. The same holds if we require only that rank M 2; see ....
L. Lovasz. On the Shannon capacity of a graph. IEEE Transactions on Information Theory, IT-25:1--7, 1979.
An Image Watermarking Scheme Based on Information Theoretic.. - Levy, Merhav (2001) (1 citation) (Correct)
....a fast maximum likelihood decoder. The BMS framework allows for ecient implementations of common watermarking schemes such as those presented in [CKLS96, CW99] as well as the implementation of a new proposed scheme named Scaled Bin Encoding (SBE) This scheme is based on theoretical work of Costa [Cos83], where a capacity achieving random coding scheme is proposed for the additive Gaussian channel with side information. The BMS implementation of the SBE scheme provides superior performance when applied to additive Gaussian information hiding systems and DCT domain image watermarking. Ecient ....
....dicult to compute. However, there are certain cases where this computation becomes simpler. These are the cases where the capacity of the system with the side information unknown to the decoder is equal to the capacity of the same system but with the side information available to the decoder. In [Cos83] Costa showed that such an equality exists in the case of additive Gaussian SIC. He proves that the additive Gaussian SIC capacity is independent of the variance of the side information variable and is equal to the capacity of the additive Gaussian channel, i.e. 2 log 2 (1 ) where P; N are ....
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M.H. Costa. Writing on dirty paper. IEEE Transactions on Information Theory, 29(3):439{ 441, May 1983.
Bounds on Achievable Rates for General.. - Khojastepour.. (2003) (Correct)
....broadcast channel (GVBC) has been considered and derived [5, 23, 27, 24] which is lower than the corresponding suggested cut set bound on the sum rate. The outer bound on this sum rate capacity is derived based on the work of Sato [21] and the achievablility part is based on Costa s precoding [8] or Marton s achievable region for the general broadcast channel [18] Some recent works on network information theory have considered the problem of multi casting in the networks which can be regarded as the network information flow. Ahlswede et al. 2, 3] introduced a new class of multiuser ....
M. H. M. Costa: Writing on dirty paper, IEEE Transactions on Information Theory, pp. 439 - 441, May (1983)
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Costa, M.H.M.: Writing on dirty paper. IEEE Transactions on Information Theory 29 (1983) 439--441
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L. Lovasz. On the Shannon capacity of a graph. IEEE Transactions on Information Theory, 25:1--7, 1979.
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L. Lovasz. On the Shannon capacity of a graph. IEEE Transactions on Information Theory, 25:1--7, 1979.
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L. Lovasz. On the Shannon capacity of a graph. IEEE Transactions on Information Theory, IT-25:1--7, 1979.
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L. Lovasz. On the Shannon capacity of a graph. IEEE Transactions on Information Theory, 25:1--7, 1979.
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The Quantum Communication Complexity of Sampling - Ambainis, Schulman, al. (1998) (15 citations) (Correct)
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L. Lovasz. On the shannon capacity of a graph. IEEE Transactions on Information theory, IT-25 (1979).
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L. Lov'asz. On the Shannon capacity of a graph. IEEE Transactions on Information Theory, IT-25:1--7, 1979.
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