Cargando…
Learnable axonal delay in spiking neural networks improves spoken word recognition
Spiking neural networks (SNNs), which are composed of biologically plausible spiking neurons, and combined with bio-physically realistic auditory periphery models, offer a means to explore and understand human auditory processing-especially in tasks where precise timing is essential. However, becaus...
Autores principales: | Sun, Pengfei, Chua, Yansong, Devos, Paul, Botteldooren, Dick |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10665570/ https://www.ncbi.nlm.nih.gov/pubmed/38027508 http://dx.doi.org/10.3389/fnins.2023.1275944 |
Ejemplares similares
-
A Neural Network Model of Lexical-Semantic Competition During Spoken Word Recognition
por: Duta, Mihaela, et al.
Publicado: (2021) -
Deep Learnability: Using Neural Networks to Quantify Language Similarity and Learnability
por: Cohen, Clara, et al.
Publicado: (2020) -
Neural dynamics of inflectional and derivational processing in spoken word comprehension: laterality and automaticity
por: Whiting, Caroline M., et al.
Publicado: (2013) -
Morphological and Whole-Word Semantic Processing Are Distinct: Event Related Potentials Evidence From Spoken Word Recognition in Chinese
por: Zou, Lijuan, et al.
Publicado: (2019) -
A Spiking Neural Network Framework for Robust Sound Classification
por: Wu, Jibin, et al.
Publicado: (2018)