Results 231 to 240 of about 77,307 (275)

Probabilistic Amplitude Shaping

Foundations and Trends® in Communications and Information Theory, 2023
Summary: Probabilistic amplitude shaping (PAS) proposed in [\textit{G. Böcherer} et al., ``Bandwidth efficient and rate-matched low-density parity-check coded modulation'', IEEE Trans. Commun. 63, No. 12, 4651--4665 (2015; \url{doi:10.1109/TCOMM.2015.2494016})] is a practical architecture for combining non-uniform distributions on higher-order ...
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Probabilistically Shaped Multicarrier Communication

2021 19th International Conference on Optical Communications and Networks (ICOCN), 2021
IM/DD probabilistically-shaped multicarrier communication is attractive for optical interconnects due to low cost and power consumption, enhanced resilience to noise and flexibility of entropy allocation. In this work, we present its principles and key features.
Mengli Liu, Mingyi Gao
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Probabilistic shaping-based delta sigma modulation

Optics Letters, 2023
This Letter proposes a probabilistic shaping delta-sigma modulation technique. By performing delta-sigma modulation on the probability shaping signal at the transmitting end, under the same transmit power and the same net bit rate, the delta-sigma modulation signal based on probability shaping can obtain better anti-noise capability than the delta ...
Li Zhao   +8 more
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Dithered probabilistic shaping

2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel, 2012
Shaping is a practical method to approximate the optimal Gaussian input distribution for a power-constrained AWGN channel. The Shaping Gain is the reduction in average constellation energy, compared to a uniform (equi-probable) cubical constellation.
Nir Palgy, Rami Zamir
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Geometrically Shaped 16QAM Outperforming Probabilistically Shaped 16QaM

2017 European Conference on Optical Communication (ECOC), 2017
We compare the proposed geometrically-shaped(GS) 16QAM with the probabilistically-shaped(PS) 16QAM formats in both numerical simulation and experimental setup. The results show that GS-16QAM outperforms PS-16QAM.
Zhen Qu, Ivan B. Djordjevic
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Probabilistic models of shape

1998
The purpose of this second part of the book is to put Active Contours into a probabilistic setting. As chapter 2 claimed, the probabilistic framework is essential for dealing with classes of shapes and motions. It is valuable even with deformable templates, in static problems, to describe classes of shapes.
Andrew Blake, Michael Isard
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