Results 41 to 50 of about 151,868 (248)

Speech Recognition on an FPGA Using Discrete and Continuous Hidden Markov Models [PDF]

, 2002
Speech recognition is a computationally demanding task, particularly the stage which uses Viterbi decoding for converting pre-processed speech data into words or sub-word units.
Melnikoff, Stephen Jonathan, Quigley, Steven Francis, Russell, Martin   +2 more
core  

What Do Large Language Models Know About Materials?

Advanced Engineering Materials, EarlyView.
If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer, Thomas Wallmersperger, Gianaurelio Cuniberti   +2 more
wiley   +1 more source

Optimal Decoding Order and Power Allocation for Sum Throughput Maximization in Downlink NOMA Systems

Entropy
In this paper, we consider a downlink non-orthogonal multiple access (NOMA) system over Nakagami-m channels. The single-antenna base station serves two single-antenna NOMA users based on statistical channel state information (CSI).
Zhuo Han, Wanming Hao, Zhiqing Tang, Shouyi Yang   +3 more
doaj   +1 more source

Real-Time Tracking of Selective Auditory Attention From M/EEG: A Bayesian Filtering Approach

Frontiers in Neuroscience, 2018
Humans are able to identify and track a target speaker amid a cacophony of acoustic interference, an ability which is often referred to as the cocktail party phenomenon.
Sina Miran, Sahar Akram, Alireza Sheikhattar, Jonathan Z. Simon, Jonathan Z. Simon, Jonathan Z. Simon, Tao Zhang, Behtash Babadi, Behtash Babadi   +8 more
doaj   +1 more source

Photoswitchable Conductive Metal–Organic Frameworks

Advanced Functional Materials, EarlyView.
A conductive material where the conductivity can be modulated remotely by irradiation with light is presented. It is based on films of conductive metal–organic framework type Cu3(HHTP)2 with embedded photochromic molecules such as azobenzene, diarylethene, spiropyran, and hexaarylbiimidazole in the pores.
Yidong Liu, Mersad Mostaghimi, Abhinav Chandresh, Saibal Jana, Wolfgang Wenzel, Lars Heinke   +5 more
wiley   +1 more source

NanoMOF‐Based Multilevel Anti‐Counterfeiting by a Combination of Visible and Invisible Photoluminescence and Conductivity

Advanced Functional Materials, EarlyView.
This study presents novel anti‐counterfeiting tags with multilevel security features that utilize additional disguise features. They combine luminescent nanosized Ln‐MOFs with conductive polymers to multifunctional mixed‐matrix membranes and powder composites. The materials exhibit visible/NIR emission and matrix‐based conductivity even as black bodies.
Moritz Maxeiner, Ruben Maile, Murat Cuvalli, Andreas Wolf, Ayisha Komal, Robert Oestreich, Christoph Janiak, Karl Mandel, Alexander Knebel, Klaus Müller‐Buschbaum   +9 more
wiley   +1 more source

Decoding Bilingual EEG Signals With Complex Semantics Using Adaptive Graph Attention Convolutional Network

IEEE Transactions on Neural Systems and Rehabilitation Engineering
Decoding neural signals of silent reading with Brain-Computer Interface (BCI) techniques presents a fast and intuitive communication method for severely aphasia patients.
Chengfang Li, Yang Liu, Jielin Li, Yuhao Miao, Jing Liu, Liang Song   +5 more
doaj   +1 more source

Intermediate Sensory Feedback Assisted Multi-Step Neural Decoding for Reinforcement Learning Based Brain-Machine Interfaces

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2022
Reinforcement-learning (RL)-based brain-machine interfaces (BMIs) interpret dynamic neural activity into movement intention without patients’ real limb movements, which is promising for clinical applications. A movement task generally requires the
Xiang Shen, Xiang Zhang, Yifan Huang, Shuhang Chen, Zhuliang Yu, Yiwen Wang   +5 more
doaj   +1 more source

A large-scale evaluation framework for EEG deep learning architectures

, 2018
EEG is the most common signal source for noninvasive BCI applications. For such applications, the EEG signal needs to be decoded and translated into appropriate actions.
Ball, Tonio, Behncke, Joos, Fiederer, Lukas D. J., Heilmeyer, Felix A., Schirrmeister, Robin T., Völker, Martin   +5 more
core   +1 more source

Onset Event Decoding Exploiting the Rhythmic Structure of Polyphonic Music [PDF]

, 2011
(c)2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or ...
Antonio Pena, Mark D. Plumbley, Matthew E. P. Davies, Norberto Degara, Student Member   +4 more
core   +2 more sources