Search Results - forward stack decoding algorithm

Low Complexity Unquantized Forward Stack Decoding Algorithm for Spinal Codes in Measurement While Drilling Communication

Authors: Xiaoyang Yu Lei Liang Ke Jiang et al.

Source: IEEE Access, Vol 13, Pp 22637-22646 (2025)

Subject Terms: Rateless codes, spinal code, low complexity decoding, Electrical engineering. Electronics. Nuclear engineering, sequential decoding, TK1-9971

Access URL: https://doaj.org/article/5853c87fe89e40ea8a224a30506b4c3f

Systems and methods for executing forward error correction decoding using a guessing random additive noise decoding algorithm

SYSTEMS AND METHODS FOR EXECUTING FORWARD ERROR CORRECTION DECODING USING A GUESSING RANDOM ADDITIVE NOISE DECODING ALGORITHM

A Low Complexity Sequential Decoding Algorithm for Rateless Spinal Codes.

Authors: Yang, Weiqiang Li, Ying Yu, Xiaopu et al.

Source: IEEE Communications Letters; Jul2015, Vol. 19 Issue 7, p1105-1108, 4p

A Modified Unquantized Fano Sequential Decoding Algorithm for Rateless Spinal Codes

Authors: Rong Sun Tingting Wang Jingwei Liu

Source: 2018 IEEE/CIC International Conference on Communications in China (ICCC). :232-236

Subject Terms: 0508 media and communications, 05 social sciences, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://dblp.uni-trier.de/db/conf/iccchina/iccchina2018.html#SunWL18

Channel coding algorithms for Ultra-Reliable Low Latency Communication

Authors: Xiang, Luping Maunder, Robert

Contributors: Xiang, Luping Maunder, Robert

Subject Terms: 621.384

Access URL: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.800840

Objective Emotion Assessment Using a Triple Attention Network for an EEG-Based Brain–Computer Interface.

Authors: Zhang, Lihua Zhang, Xin Zhang, Xiu et al.

Source: Brain Sciences (2076-3425); Nov2025, Vol. 15 Issue 11, p1167, 31p

Subject Terms: ELECTROENCEPHALOGRAPHY, EMOTION recognition, ALGORITHMS, NEURAL computers, ARTIFICIAL neural networks, BRAIN-computer interfaces, AFFECTIVE computing

Fast Inference via Hierarchical Speculative Decoding

Authors: Mohri, Clara Kaplan, Haim Schuster, Tal et al.

Subject Terms: Machine Learning

Relation: http://arxiv.org/abs/2510.19705

Availability: http://arxiv.org/abs/2510.19705

A Low Complexity Sequential Decoding Algorithm for Rateless Spinal Codes

Authors: Ying Li Xiaopu Yu Weiqiang Yang et al.

Source: IEEE Communications Letters. 19:1105-1108

Subject Terms: 0203 mechanical engineering, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

Access URL: https://ieeexplore.ieee.org/document/7113798/
http://dblp.uni-trier.de/db/journals/icl/icl19.html#YangLYL15
https://dblp.uni-trier.de/db/journals/icl/icl19.html#YangLYL15

The Diet–Obesity–Brain Axis: Metabolic, Epigenetic, and DNA-Repair Pathways Linking Eating Patterns to Cognitive Aging, with an AI-Enabled Translational Perspective.

Authors: Loomba, Manish Bansal, Sanjeev Singh, Krishna Kumar et al.

Source: Nutrients. Nov2025, Vol. 17 Issue 21, p3493. 20p.

Autoencoder-based confidence score for item preknowledge detection.

Authors: Pan, Yiqin

Source: Behaviormetrika; Jul2025, Vol. 52 Issue 2, p317-342, 26p

Subject Terms: AUTOENCODERS, DEEP learning, PRIOR learning, SIMULATION methods & models, DETECTION algorithms, SIGNAL detection, TEST design

Decoding emotions and unveiling stress: a non-invasive approach through sequential feature extraction and multiclass classifiers.

Authors: Upadhaya, Shraddha Brahma, Biswajit K.S, Hareesha et al.

Source: Health & Technology; Nov2024, Vol. 14 Issue 6, p1149-1160, 12p

Shift-Reduce Task-Oriented Semantic Parsing with Stack-Transformers.

Authors: Fernández-González, Daniel

Source: Cognitive Computation; Nov2024, Vol. 16 Issue 6, p2846-2862, 17p

Automated Age Estimation from OPG Images and Patient Records Using Deep Feature Extraction and Modified Genetic–Random Forest.

Authors: Ozlu Ucan, Gulfem Gwassi, Omar Abboosh Hussein Apaydin, Burak Kerem et al.

Source: Diagnostics (2075-4418); Feb2025, Vol. 15 Issue 3, p314, 27p

Subject Terms: CONVOLUTIONAL neural networks, RANDOM forest algorithms, FORENSIC sciences, ARTIFICIAL intelligence, DEEP learning

Decoding Movement From Electrocorticographic Activity: A Review.

Authors: Volkova, Ksenia Lebedev, Mikhail A. Kaplan, Alexander et al.

Source: Frontiers in Neuroinformatics; 12/3/2019, Vol. 13, p1-20, 20p

Subject Terms: BRAIN-computer interfaces, ELECTROENCEPHALOGRAPHY, DECODING algorithms, RESEARCH teams, NEUROPROSTHESES

SC-Fano Decoding of Polar Codes

Authors: Jeong, Min-Oh Hong, Song-Nam

Index Terms: Electrical Engineering and Systems Science - Signal Processing, Computer Science - Information Theory, text

URL: http://arxiv.org/abs/1901.06791

DCNN-WiGRF: Depression Recognition through Deep Feature Extraction using Deep Learning and weight updated information gain Random Forest technique.

Authors: Meshram, Pratiksha Rambola, Radhakrishna

Source: Frontiers in Health Informatics; 2024, Vol. 13 Issue 3, p9162-9178, 17p

Subject Terms: RANDOM forest algorithms, FEATURE extraction, COMPUTATIONAL intelligence, DATA augmentation, BIPOLAR disorder

Sequential Decoding of Multiple Traces Over the Syndrome Trellis for Synchronization Errors

Authors: Banerjee, Anisha Welter, Lorenz Amat, Alexandre Graell i et al.

Index Terms: Computer Science - Information Theory, text

URL: http://arxiv.org/abs/2410.07120

Facial emotion recognition using deep quantum and advanced transfer learning mechanism.

Authors: Alsubai, Shtwai Alqahtani, Abdullah Alanazi, Abed et al.

Source: Frontiers in Computational Neuroscience; 2024, p1-19, 19p

Subject Terms: EMOTION recognition, FACIAL expression & emotions (Psychology), FACIAL expression, ARTIFICIAL intelligence, QUANTUM computing

Point completion by a Stack‐Style Folding Network with multi‐scaled graphical features.

Authors: Rao, Yunbo Xu, Ping Zeng, Shaoning et al.

Source: IET Computer Vision (Wiley-Blackwell); Aug2023, Vol. 17 Issue 5, p576-585, 10p

Subject Terms: POINT cloud, FEATURE extraction, COMPUTER vision