Results 21 to 30 of about 46,112 (290)
Decoding fMRI alcohol cue reactivity and its association with drinking behaviour
BMJ Mental Health, 2023 Background Cue reactivity, the enhanced sensitivity to conditioned cues, is associated with habitual and compulsive alcohol consumption. However, most previous studies in alcohol use disorder (AUD) compared brain activity between alcohol and neutral ...
Martin Fungisai Gerchen +8 more
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Improved Recurrent Neural Network based BP Decoding Algorithm for Polar Codes
Guangtongxin yanjiu, 2022 In recent years, the emerging Deep Learning (DL) technology has made progress in the field of decoding. Current polar code neural network decoder has faster convergence speed and better Bit Error Rate (BER) performance than Belief Propagation (BP ...
Xue-lu DENG, Da-qin PENG
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2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2018 Lattice decoders constructed with neural networks are presented. Firstly, we show how the fundamental parallelotope is used as a compact set for the approximation by a neural lattice decoder. Secondly, we introduce the notion of Voronoi-reduced lattice basis.
Vincent Corlay +3 more
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Neural Decoder for Topological Codes
Physical Review Letters, 2017 We present an algorithm for error correction in topological codes that exploits modern machine learning techniques. Our decoder is constructed from a stochastic neural network called a Boltzmann machine, of the type extensively used in deep learning.
Torlai, Giacomo, Melko, Roger G.
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Decoding neural responses to motion-in-depth using EEG [PDF]
, 2020 MH was supported by the European Union’s Horizon 2020 Research and Innovation Program under the Marie Skłodowska-Curie grant agreement no. 641805. AW was supported by United Kingdom Biotechnology and Biological Science Research Council (BBSRC) grant ...
Himmelberg, Marc M +9 more
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Graph-Based Codes and Iterative Decoding [PDF]
, 2003 The field of error correcting codes was revolutionized by the introduction of turbo codes in 1993. These codes demonstrated dramatic performance improvements over any previously known codes, with significantly lower complexity.
Khandekar, Aamod Dinkar
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PLoS ONE, 2022 Rapidly developing technology for large scale neural recordings has allowed researchers to measure the activity of hundreds to thousands of neurons at single cell resolution in vivo.
Charles R Heller, Stephen V David
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Neural Decoding With Optimization of Node Activations
IEEE Communications Letters, 2022 IEEE Communications ...
Eliya Nachmani, Yair Be'ery
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Deep Neural Network Based Reconciliation for CV-QKD
Photonics, 2022 High-speed reconciliation is indispensable for supporting the continuous-variable quantum key distribution (CV-QKD) system to generate the secure key in real-time. However, the error correction process’s high complexity and low processing speed limit the
Jun Xie +3 more
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An Empirical Study of Encoders and Decoders in Graph-Based Dependency Parsing
IEEE Access, 2020 Graph-based dependency parsing consists of two steps: first, an encoder produces a feature representation for each parsing substructure of the input sentence, which is then used to compute a score for the substructure; and second, a decoder finds the ...
Ge Wang, Ziyuan Hu, Zechuan Hu, Kewei Tu
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