958 resultados para Decoding principle


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Over the last 50 yr, thermal biology has shifted from a largely physiological science to a more integrated science of behavior, physiology, ecology, and evolution. Today, the mechanisms that underlie responses to environmental temperature are being scrutinized at levels ranging from genes to organisms. From these investigations, a theory of thermal adaptation has emerged that describes the evolution of thermoregulation, thermal sensitivity, and thermal acclimation. We review and integrate current models to form a conceptual model of coadaptation. We argue that major advances will require a quantitative theory of coadaptation that predicts which strategies should evolve in specific thermal environments. Simply combining current models, however, is insufficient to understand the responses of organisms to thermal heterogeneity; a theory of coadaptation must also consider the biotic interactions that influence the net benefits of behavioral and physiological strategies. Such a theory will be challenging to develop because each organism's perception of and response to thermal heterogeneity depends on its size, mobility, and life span. Despite the challenges facing thermal biologists, we have never been more pressed to explain the diversity of strategies that organisms use to cope with thermal heterogeneity and to predict the consequences of thermal change for the diversity of communities.

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Complex numbers appear in the Hilbert space formulation of quantum mechanics, but not in the formulation in phase space. Quantum symmetries are described by complex, unitary or antiunitary operators defining ray representations in Hilbert space, whereas in phase space they are described by real, true representations. Equivalence of the formulations requires that the former representations can be obtained from the latter and vice versa. Examples are given. Equivalence of the two formulations also requires that complex superpositions of state vectors can be described in the phase space formulation, and it is shown that this leads to a nonlinear superposition principle for orthogonal, pure-state Wigner functions. It is concluded that the use of complex numbers in quantum mechanics can be regarded as a computational device to simplify calculations, as in all other applications of mathematics to physical phenomena.

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Ab initio density functional theory (DFT) calculations are performed to study the adsorption of H-2 molecules on a Ti-doped Mg(0001) surface. We find that two hydrogen molecules are able to dissociate on top of the Ti atom with very small activation barriers (0.103 and 0.145 eV for the first and second H-2 molecules, respectively). Additionally, a molecular adsorption state of H-2 above the Ti atom is observed for the first time and is attributed to the polarization of the H-2 molecule by the Ti cation. Our results parallel recent findings for H-2 adsorption on Ti-doped carbon nanotubes or fullerenes. They provide new insight into the preliminary stages of hydrogen adsorption onto Ti-incorporated Mg surfaces.

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The Australian beef industry places the greatest value in bulls, in comparison to cows, for prime beef production. Male carcasses can be sold for a larger profit due to their increased muscle mass. This project aims to demonstrate the feasibility of producing male animals that can sire male only offspring, through a transgenic approach in mice that could later be translated into livestock production systems. The mouse Sry (Sex determining region on the Y) gene has been shown to provide the initiating molecular signal leading to male sex determination in mammals. Sry has also been shown to cause sex reversal in XX mice transgenic for the gene. In this project Sry will be targeted to a locus not subject to X-inactivation on the X chromosome of XY mice. These mice will be bred to determine how the transgene is passed on, to determine expression of the transgene, and to assess its activity in causing XX sex reversal. The male mice transgenic for the Sry gene on their X chromosome will be produced using tetraploid aggregation, which in a single step produces 100% ES cell derived embryos. The same target locus can later be used to introduce the bovine SRY gene onto the X chromosome of bovidae species and using germ cell transplantation produce sex reversed animals. This would bypass the need for expensive chimera crosses and provide farmers with a stud bull capable of producing only sons.

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We present a novel, maximum-likelihood (ML), lattice-decoding algorithm for noncoherent block detection of QAM signals. The computational complexity is polynomial in the block length; making it feasible for implementation compared with the exhaustive search ML detector. The algorithm works by enumerating the nearest neighbor regions for a plane defined by the received vector; in a conceptually similar manner to sphere decoding. Simulations show that the new algorithm significantly outperforms existing approaches

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Despite extensive progress on the theoretical aspects of spectral efficient communication systems, hardware impairments, such as phase noise, are the key bottlenecks in next generation wireless communication systems. The presence of non-ideal oscillators at the transceiver introduces time varying phase noise and degrades the performance of the communication system. Significant research literature focuses on joint synchronization and decoding based on joint posterior distribution, which incorporate both the channel and code graph. These joint synchronization and decoding approaches operate on well designed sum-product algorithms, which involves calculating probabilistic messages iteratively passed between the channel statistical information and decoding information. Channel statistical information, generally entails a high computational complexity because its probabilistic model may involve continuous random variables. The detailed knowledge about the channel statistics for these algorithms make them an inadequate choice for real world applications due to power and computational limitations. In this thesis, novel phase estimation strategies are proposed, in which soft decision-directed iterative receivers for a separate A Posteriori Probability (APP)-based synchronization and decoding are proposed. These algorithms do not require any a priori statistical characterization of the phase noise process. The proposed approach relies on a Maximum A Posteriori (MAP)-based algorithm to perform phase noise estimation and does not depend on the considered modulation/coding scheme as it only exploits the APPs of the transmitted symbols. Different variants of APP-based phase estimation are considered. The proposed algorithm has significantly lower computational complexity with respect to joint synchronization/decoding approaches at the cost of slight performance degradation. With the aim to improve the robustness of the iterative receiver, we derive a new system model for an oversampled (more than one sample per symbol interval) phase noise channel. We extend the separate APP-based synchronization and decoding algorithm to a multi-sample receiver, which exploits the received information from the channel by exchanging the information in an iterative fashion to achieve robust convergence. Two algorithms based on sliding block-wise processing with soft ISI cancellation and detection are proposed, based on the use of reliable information from the channel decoder. Dually polarized systems provide a cost-and spatial-effective solution to increase spectral efficiency and are competitive candidates for next generation wireless communication systems. A novel soft decision-directed iterative receiver, for separate APP-based synchronization and decoding, is proposed. This algorithm relies on an Minimum Mean Square Error (MMSE)-based cancellation of the cross polarization interference (XPI) followed by phase estimation on the polarization of interest. This iterative receiver structure is motivated from Master/Slave Phase Estimation (M/S-PE), where M-PE corresponds to the polarization of interest. The operational principle of a M/S-PE block is to improve the phase tracking performance of both polarization branches: more precisely, the M-PE block tracks the co-polar phase and the S-PE block reduces the residual phase error on the cross-polar branch. Two variants of MMSE-based phase estimation are considered; BW and PLP.

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We employ two different methods, based on belief propagation and TAP,for decoding corrupted messages encoded by employing Sourlas's method, where the code word comprises products of K bits selected randomly from the original message. We show that the equations obtained by the two approaches are similar and provide the same solution as the one obtained by the replica approach in some cases K=2. However, we also show that for K>=3 and unbiased messages the iterative solution is sensitive to the initial conditions and is likely to provide erroneous solutions; and that it is generally beneficial to use Nishimori's temperature, especially in the case of biased messages.

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Statistical physics is employed to evaluate the performance of error-correcting codes in the case of finite message length for an ensemble of Gallager's error correcting codes. We follow Gallager's approach of upper-bounding the average decoding error rate, but invoke the replica method to reproduce the tightest general bound to date, and to improve on the most accurate zero-error noise level threshold reported in the literature. The relation between the methods used and those presented in the information theory literature are explored.

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The performance of "typical set (pairs) decoding" for ensembles of Gallager's linear code is investigated using statistical physics. In this decoding method, errors occur, either when the information transmission is corrupted by atypical noise, or when multiple typical sequences satisfy the parity check equation as provided by the received corrupted codeword. We show that the average error rate for the second type of error over a given code ensemble can be accurately evaluated using the replica method, including the sensitivity to message length. Our approach generally improves the existing analysis known in the information theory community, which was recently reintroduced in IEEE Trans. Inf. Theory 45, 399 (1999), and is believed to be the most accurate to date. © 2002 The American Physical Society.

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We determine the critical noise level for decoding low density parity check error correcting codes based on the magnetization enumerator , rather than on the weight enumerator employed in the information theory literature. The interpretation of our method is appealingly simple, and the relation between the different decoding schemes such as typical pairs decoding, MAP, and finite temperature decoding (MPM) becomes clear. In addition, our analysis provides an explanation for the difference in performance between MN and Gallager codes. Our results are more optimistic than those derived via the methods of information theory and are in excellent agreement with recent results from another statistical physics approach.