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Role of Brainwaves in Neural Speech Decoding
2020 28th European Signal Processing Conference (EUSIPCO), 2021Neural speech decoding aims at direct decoding of speech from the brain to restore speech communication in patients with locked-in syndrome (fully paralyzed but aware). Despite the recent progress, exactly which aspects of neural activities are characterizing the decoding process is still unclear. Neural oscillations have been associated with playing a
Debadatta Dash +2 more
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A neural network for predicting decoder error in turbo decoders
IEEE Communications Letters, 1999It is shown that a neural network can be trained to predict the presence of errors in turbo-decoded data. The inputs to the network are samples of the cross entropy of the component decoder outputs at two or more time instants. Such a neural network can be used as a trigger for retransmission requests at either the beginning or at the conclusion of the
Michael Eoin Buckley, Stephen B. Wicker
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A neural decoding strategy based on convolutional neural network
Journal of Intelligent & Fuzzy Systems, 2020Neural decoding is a technology to analyze intentions produced by neural activities, which has important applications in military, medical, entertainment and so on. As a typical application, decoding electromyogram (EMG) signals into corresponding gestures is an important content. In order to improve the accuracy of EMG signals recognition, researchers
Shaoyang Hua, Congqing Wang, Xuewei Wu
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Tree-structured neural decoding
J. Mach. Learn. Res., 2003Summary: We propose adaptive testing as a general mechanism for extracting information about stimuli from spike trains. Each test or question corresponds to choosing a neuron and a time interval and checking for a given number of spikes. No assumptions are made about the distribution of spikes or any other aspect of neural encoding.
Christian d'Avignon, Donald Geman
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Neural decoders with permutation invariant structure
Journal of the Franklin Institute, 2023zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xiangyu Chen, Min Ye 0005
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An artificial neural net Viterbi decoder
IEEE Transactions on Communications, 1996The Viterbi algorithm is a maximum likelihood means for decoding convolutional codes and has thus played an important role in applications ranging from satellite communications to cellular telephony. In the past, Viterbi decoders have usually been implemented using digital circuits.
Xiao-an Wang, Stephen B. Wicker
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Decoding Visual Neural Representations by Multimodal Learning of Brain-Visual-Linguistic Features
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023Changde Du, Jinpeng Li, Huiguang He
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Structured Neural Decoding With Multitask Transfer Learning of Deep Neural Network Representations
IEEE Transactions on Neural Networks and Learning Systems, 2022Changying Du +2 more
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Neural decoding of continuous upper limb movements: a meta-analysis
Disability and Rehabilitation: Assistive Technology, 2022Ali Fallah, Ali Maleki
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