Highly Efficient Classification of Time‐Series Based on Resistive Switching Cluster‐Assembled Materials

The need for high accuracy time‐series classification and pattern recognition tasks is rapidly increasing due to the ubiquitous deployment of the internet of things (IoT) paradigm, such as in the development of brain–computer interfaces. Several statistical methods have been proposed for the analysi...

全面介紹

書目詳細資料

Principais autores:	Filippo Profumo, Francesca Borghi, Tommaso Angì, Marta Maschietto, Stefano Vassanelli, Paolo Milani
格式:	Artigo
語言:	Inglês
出版:	Wiley 2025-12-01
叢編:	Advanced Intelligent Systems
主題:	brain–computer interface nanostructured materials negative differential resistance neuromorphic devices resistive switching time‐series classifiers
在線閱讀:	https://doi.org/10.1002/aisy.202401150
標簽:	添加標簽 沒有標簽, 成為第一個標記此記錄!