19,187 research outputs found
Learning Semantic Representations for the Phrase Translation Model
This paper presents a novel semantic-based phrase translation model. A pair
of source and target phrases are projected into continuous-valued vector
representations in a low-dimensional latent semantic space, where their
translation score is computed by the distance between the pair in this new
space. The projection is performed by a multi-layer neural network whose
weights are learned on parallel training data. The learning is aimed to
directly optimize the quality of end-to-end machine translation results.
Experimental evaluation has been performed on two Europarl translation tasks,
English-French and German-English. The results show that the new semantic-based
phrase translation model significantly improves the performance of a
state-of-the-art phrase-based statistical machine translation sys-tem, leading
to a gain of 0.7-1.0 BLEU points
Channel Acquisition for Massive MIMO-OFDM with Adjustable Phase Shift Pilots
We propose adjustable phase shift pilots (APSPs) for channel acquisition in
wideband massive multiple-input multiple-output (MIMO) systems employing
orthogonal frequency division multiplexing (OFDM) to reduce the pilot overhead.
Based on a physically motivated channel model, we first establish a
relationship between channel space-frequency correlations and the channel power
angle-delay spectrum in the massive antenna array regime, which reveals the
channel sparsity in massive MIMO-OFDM. With this channel model, we then
investigate channel acquisition, including channel estimation and channel
prediction, for massive MIMO-OFDM with APSPs. We show that channel acquisition
performance in terms of sum mean square error can be minimized if the user
terminals' channel power distributions in the angle-delay domain can be made
non-overlapping with proper phase shift scheduling. A simplified pilot phase
shift scheduling algorithm is developed based on this optimal channel
acquisition condition. The performance of APSPs is investigated for both one
symbol and multiple symbol data models. Simulations demonstrate that the
proposed APSP approach can provide substantial performance gains in terms of
achievable spectral efficiency over the conventional phase shift orthogonal
pilot approach in typical mobility scenarios.Comment: 15 pages, 4 figures, accepted for publication in the IEEE
Transactions on Signal Processin
Double neutron-proton differential transverse flow as a probe for the high-density behavior of the nuclear symmetry energy
The double neutron-proton differential transverse flowtaken from two reaction
systems using different isotopes of the same element is studied at incident
beam energies of 400 and 800 MeV/nucleon within the framework of an isospin-
and momentum-dependent hadronic transport model IBUU04. The double differential
flow is found to retain about the same sensitivity to the density dependence of
the nuclear symmetry energy as the single differential flow in the more
neutron-rich reaction. Because the double differential flow reduces
significantly both the systematic errors and the influence of the Coulomb
force, it is thus more effective probe for the high-density behavior of the
nuclear symmetry energy.Comment: 12 pages, 6 figures, version accepted for publication in Phys. Rev.
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