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Monte Carlo Algorithms for the Partition Function and Information Rates of Two-Dimensional Channels
[article]
2012
arXiv
pre-print
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The paper proposes Monte Carlo algorithms for the computation of the information rate of two-dimensional source/channel models. ...
Both problems can be reduced to computing a Monte Carlo estimate of a partition function. The proposed algorithms use tree-based Gibbs sampling and multilayer (multitemperature) importance sampling. ...
The authors also wish to thank David MacKay and Iain Murray for pointing out to us [24] , and the reviewers and the Associate Editor for helpful comments. ...
arXiv:1105.5542v2
fatcat:qzacmvbf3jfdja6bcxccvl6wse
Monte Carlo Algorithms for the Partition Function and Information Rates of Two-Dimensional Channels
2013
IEEE Transactions on Information Theory
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The paper proposes Monte Carlo algorithms for the computation of the information rate of two-dimensional source / channel models. ...
Both problems can be reduced to computing a Monte Carlo estimate of a partition function. The proposed algorithms use tree-based Gibbs sampling and multilayer (multitemperature) importance sampling. ...
The authors also wish to thank David MacKay and Iain Murray for pointing out to us [24] , and the reviewers and the Associate Editor for helpful comments. ...
doi:10.1109/tit.2012.2212413
fatcat:eb5kvbcrinhg5ies5abhknt5zy
Capacity estimation of two-dimensional channels using Sequential Monte Carlo
2014
2014 IEEE Information Theory Workshop (ITW 2014)
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We derive a new Sequential-Monte-Carlo-based algorithm to estimate the capacity of two-dimensional channel models. ...
The proposed algorithm is profiled against a state-of-the-art method, yielding more than an order of magnitude improvement in estimation accuracy for a given computation time. ...
ACKNOWLEDGMENT Supported by the projects Probabilistic modeling of dynamical systems (Contract number: 621-2013-5524) and Learning of complex dynamical systems (Contract number: 637-2014-466), both funded ...
doi:10.1109/itw.2014.6970868
dblp:conf/itw/NaessethLS14
fatcat:oegp5log5naqjgtlyv57hggfmu
Capacity estimation of two-dimensional channels using Sequential Monte Carlo
[article]
2014
arXiv
pre-print
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We derive a new Sequential-Monte-Carlo-based algorithm to estimate the capacity of two-dimensional channel models. ...
The proposed algorithm is profiled against a state-of-the-art method, yielding more than an order of magnitude improvement in estimation accuracy for a given computation time. ...
Our main contribution is a new algorithm, based on sequential Monte Carlo (SMC) methods, for numerically estimating the capacity of two-dimensional channels. ...
arXiv:1405.0102v2
fatcat:mzsfswwu7jfojn5pemqaledn7e
Simulation-based estimation of the partition function and the information rate of two-dimensional models
2008
2008 IEEE International Symposium on Information Theory
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Monte Carlo methods are considered to compute, first, the partition function of graphical models, and second, the information rate of source/channel models, in both cases for factor graphs with cycles. ...
The convergence of two basic Monte Carlo methods is improved by sampling only a cycle breaking subset of the variables and using exact sum-product computations for the remaining variables. ...
These methods are then applied to two specific examples: the partition function of an Ising model in Section III and the information rate of a two-dimensional intersymbol interference channel in Section ...
doi:10.1109/isit.2008.4595160
dblp:conf/isit/LoeligerM08
fatcat:2mpnxv4v7bbq5os6hz3tlvu4iy
Convergence Analysis for Sequential Monte Carlo Receivers in Communications Applications
2006
2006 IEEE 12th Digital Signal Processing Workshop & 4th IEEE Signal Processing Education Workshop
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Recently, sequential Monte Carlo methods have been applied in the telecommunications field and found application in receiver design. ...
In this work we investigate the convergence properties of these algorithms when utilized in various types of receivers. We quantify the convergence rate. ...
CONVERGENCE OF SEQUENTIAL MONTE CARLO ALGORITHM The trajectory of each particle in SMC algorithms can be viewed as a realization of a Markov chain. ...
doi:10.1109/dspws.2006.265405
fatcat:k6chzbkrqndadkhu76zakzsxba
MOEA design of robust digital symbol sets
2005
Proceedings of the 2005 conference on Genetic and evolutionary computation - GECCO '05
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Investigated 1 is the ability of a Multiobjective Evolutionary Algorithm (MOEA), the multiobjective fast messy GA (MOMGA-IIa), to optimize two dimensional (4, 8,. .., and 256)-ary symbol set design for ...
In fact, the ultimate goal would be to have a channel noise probe identify the noise over a channel and back propagates this information to an EA that searches for an optimal symbol set for that channel ...
doi:10.1145/1068009.1068380
dblp:conf/gecco/DayNL05
fatcat:uodx22lcbfbsnao35teczvjawu
MOEA design of robust digital symbol sets
2005
Proceedings of the 2005 workshops on Genetic and evolutionary computation - GECCO '05
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Investigated 1 is the ability of a Multiobjective Evolutionary Algorithm (MOEA), the multiobjective fast messy GA (MOMGA-IIa), to optimize two dimensional (4, 8,. .., and 256)-ary symbol set design for ...
In fact, the ultimate goal would be to have a channel noise probe identify the noise over a channel and back propagates this information to an EA that searches for an optimal symbol set for that channel ...
doi:10.1145/1102256.1102294
dblp:conf/gecco/DayNL05a
fatcat:ddxy5zkrkbeunl4mwqbgbgzcoy
Multi-cell MIMO Downlink with Fairness Criteria: the Large System Limit
[article]
2010
arXiv
pre-print
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The proposed method is computationally much more efficient than Monte Carlo simulation and provides a very accurate approximation (almost indistinguishable) for the actual finite-dimensional case, even ...
for of a small number of users and base station antennas. ...
mean user rates of each group) in the large system limit as a function of group locations and compares them with the achievable rates obtained by Monte Carlo simulation in finite dimensions with N = 1 ...
arXiv:1001.1133v2
fatcat:zlcfthdhhra2lhndnohy66qn7u
Maximizing the Biochemical Resolving Power of Fluorescence Microscopy
2013
PLoS ONE
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We describe optimized imaging protocols, provide optimization algorithms and describe precision and resolving power in biochemical imaging thanks to the analysis of the general properties of Fisher information ...
This theoretical foundation leads to a generalized strategy for the optimization of multi-dimensional optical detection, and demonstrates how the parallel detection of all properties of fluorescence can ...
Acknowledgments We would like to thank Emma Kay Richardson for supplying the HeLa cells expressing EGFP-actin and EYFP-tubulin.
Author Contributions Conceived and designed the experiments: AE ARV. ...
doi:10.1371/journal.pone.0077392
pmid:24204821
pmcid:PMC3810478
fatcat:t4l5jd2l6zeb5kszw3ovmqvff4
Extending Monte Carlo Methods to Factor Graphs with Negative and Complex Factors
[article]
2012
arXiv
pre-print
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The partition function of a factor graph can sometimes be accurately estimated by Monte Carlo methods. In this paper, such methods are extended to factor graphs with negative and complex factors. ...
The authors would also like to thank Pascal Vontobel for his helpful comments on an earlier draft of this paper. ...
ACKNOWLEDGEMENT The first author would like to thank Radford Neal, Ruslan Salakhutdinov, and Neal Madras for helpful discussions. ...
arXiv:1206.5232v2
fatcat:czw774sqordlhgcnyfm6x7gjze
Extending monte carlo methods to factor graphs with negative and complex factors
2012
2012 IEEE Information Theory Workshop
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The partition function of a factor graph can sometimes be accurately estimated by Monte Carlo methods. In this paper, such methods are extended to factor graphs with negative and complex factors. ...
The first author would like to thank Radford Neal, Ruslan Salakhutdinov, and Neal Madras for helpful discussions. ...
The authors would also like to thank Pascal Vontobel for his helpful comments on an earlier draft of this paper. ...
doi:10.1109/itw.2012.6404694
dblp:conf/itw/MolkaraieL12
fatcat:mosdnokk5jehfhnczhdlfrjffy
Estimating the information rate of noisy two-dimensional constrained channels
2010
2010 IEEE International Symposium on Information Theory
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The problem of computing the information rate of noisy two-dimensional constrained source / channel models has been an unsolved problem. ...
The second method uses generalized belief propagation and is shown to yield a good approximation of the information rate. ...
For two-dimensional (2-D) noisy constrained source / channel models, however, computing the information rate has remained an unsolved problem. ...
doi:10.1109/isit.2010.5513320
dblp:conf/isit/MolkaraieL10
fatcat:vmufcydwjff4bg23p3s34cgmf4
Variable rate multitone system for multipath fading channels
1998
Electronics Letters
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To obtain a target BER and maximum aggregated rate, each subcarrier bit rate is modified independently to adjust the transmitted signal to the spectral channel shape and to track the channel variations ...
Spectral efficiency and the required feedback channel capacity are obtained through simulation over a multipath Rician channel. ...
The adaptation algorithm evaluates the channel quality and provides a suitable constellation size for each subcarrier as a function of the distance needed among symbols for a target BER and a performance ...
doi:10.1049/el:19980900
fatcat:wh2ddfgwzbg7tfgippyxpqsccy
Low-complexity Voronoi shaping for the Gaussian channel
[article]
2021
arXiv
pre-print
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A mutual information estimation method and a log-likelihood approximation method based on importance sampling for very large constellations are proposed and applied to the designed VCs. ...
With error-control coding, the proposed VCs can have higher achievable information rates than the conventional scaled VCs because of their inherently good pseudo-Gray labeling feature, with a lower decoding ...
ACHIEVABLE INFORMATION RATES AIRs indicate the maximum amount of information that can be transmitted reliably over the underlying channel. ...
arXiv:2106.03262v2
fatcat:2br6zenrlrabrjy777z5dul2da
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