We address the problem of aligning multiple medical event sequences, corresponding to different clinical narratives, comparing the following approaches: (1) A novel weighted finite state transducer representation of medical event sequences that enables composition and search for decoding, and (2) ...
Previous research has primarily employed deep learning models such as Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs) for decoding imagined character signals. These approaches have treated the temporal and spatial features of the signals in a sequential, parallel, or single...
展开 关键词: Deep learning Time-frequency analysis Correlation Conferences Speech enhancement Decorrelation Decoding Delays Transient analysis Time-domain analysis 会议名称: 2024 18th International Workshop on Acoustic Signal Enhancement (IWAENC) 主办单位: IEEE 收藏...
Motor Imagery (MI) EEG decoding is crucial in Brain-Computer Interface (BCI) technology, facilitating direct communication between the brain and external devices. However, accurately capturing temporal dependencies in MI EEG signals, especially in subject-independent MI-BCIs, remains a persistent ...
A decoding process for this temporal coding is proposed in which neurons work in a correlator mode. In the case of motion analysis, periodic resetting ... O Parodi,P Combe,JC Ducom - 《Biological Cybernetics》 被引量: 47发表: 1996年 加载更多0...
This observation suggests a natural instantaneous CC (ICC) estimator as required for high temporal resolution and real-time ensemble analysis and decoding. Results are shown in simulated data sets and neural activity of rat motor cortical neurons during a behavioral task....
The TCAFU integrates high-level and low-level features and passes the fused features to the subsequent decoding process. 3.2. Multi-Branch Feature Extraction Block High-quality feature extraction enables the model to capture complex spatiotemporal evolution patterns from radar echo data, thereby enhanci...