Results 31 to 40 of about 2,367,946 (319)
Applied Sciences, 2023 Channel neural decoding is very promising as it outperforms the traditional channel decoding algorithms. Unfortunately, it still faces the disadvantage of high computational complexity and storage complexity compared with the traditional decoding ...
Qingle Wu +4 more
doaj +1 more source
Multivariate neural decoding performance. [PDF]
, 2022 Multivariate neural decoding performance.
Clinton D. Kilts (228932) +1 more
core +1 more source
Frontiers in Human Neuroscience, 2022 Establishing the basic knowledge, methodology, and technology for a framework for the continuous decoding of hand/arm movement intention was the aim of the ERC-funded project “Feel Your Reach”. In this work, we review the studies and methods we performed
Gernot R. Müller-Putz +15 more
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Visual Representations: Insights from Neural Decoding.
Annual Review of Vision Science, 2023 Patterns of brain activity contain meaningful information about the perceived world. Recent decades have welcomed a new era in neural analyses, with computational techniques from machine learning applied to neural data to decode information represented ...
Amanda K. Robinson, G. Quek, T. Carlson
semanticscholar +1 more source
Robust neural decoding for dexterous control of robotic hand kinematics
Comput. Biol. Medicine, 2023 BACKGROUND Manual dexterity is a fundamental motor skill that allows us to perform complex daily tasks. Neuromuscular injuries, however, can lead to the loss of hand dexterity.
Jiahao Fan +3 more
semanticscholar +1 more source
Firing-rate-modulated spike detection and neural decoding co-design
bioRxiv, 2023 Objective. Translational efforts on spike-signal-based implantable brain-machine interfaces (BMIs) are increasingly aiming to minimise bandwidth while maintaining decoding performance.
Zheng Zhang, Tim Constandinou
semanticscholar +1 more source
On-FPGA Spiking Neural Networks for End-to-End Neural Decoding
IEEE Access, 2023 In the last decades, deep learning neural decoding algorithms have gained momentum in the field of neural interfaces and neural processing systems. However, to be deployed on low-budget portable devices while maintaining real-time operability, these ...
Gianluca Leone, L. Raffo, P. Meloni
semanticscholar +1 more source
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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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
openaire +2 more sources
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
doaj +3 more sources