Results 151 to 160 of about 174,824 (351)
Flexible Memory: Progress, Challenges, and Opportunities
Flexible memory technology is crucial for flexible electronics integration. This review covers its historical evolution, evaluates rigid systems, proposes a flexible memory framework based on multiple mechanisms, stresses material design's role, presents a coupling model for performance optimization, and points out future directions.
Ruizhi Yuan +5 more
wiley +1 more source
Advances in Organic In‐Sensor Neuromorphic Computing: from Material Mechanisms to Applications
This review discusses organic in‐sensor neuromorphic computing for wearable and bioelectronic systems, with a focus on memory‐based and OECT‐based synaptic devices. It highlights key design principles, recent advances, and existing challenges. By integrating sensing and processing within organic materials, the approach enables real‐time, low‐power, and
Dong Hyun Lee +3 more
wiley +1 more source
Bilateral inhibition by glycinergic afferents in the medial superior olive [PDF]
Grothe, Benedikt, Sanes, Dan H.
core +1 more source
Memristors based on trimethylsulfonium (phenanthroline)tetraiodobismuthate have been utilised as a nonlinear node in a delayed feedback reservoir. This system allowed an efficient classification of acoustic signals, namely differentiation of vocalisation of the brushtail possum (Trichosurus vulpecula).
Ewelina Cechosz +4 more
wiley +1 more source
Near‐infrared reservoir computing system has been realized by using α‐In2Se3 optoelectronic device with concise device and algorithm architecture, achieving high accuracy near 100% and noise robustness in face recognition tasks. These findings demonstrate 2D ferroelectric device‐based optoelectronic RC system as a compact and efficient computing ...
Wenyu Songlu +15 more
wiley +1 more source
Nicotinic and Muscarinic Reduction of Unitary Excitatory Postsynaptic Potentials in Sensory Cortex; Dual Intracellular Recording In Vitro [PDF]
Robert B. Levy +2 more
openalex +1 more source
Bioinspired Fully On‐Chip Learning Implemented on Memristive Neural Networks
This work proposes a memristive neural network based on van der Waals ferroelectric memristors and contrastive Hebbian learning, enabling fully on‐chip learning. The system achieves over 98% accuracy in pattern recognition with low power consumption (0.321 nJ/image) and high robustness, paving the way for efficient, bioinspired neuromorphic computing ...
Zhixing Wen +9 more
wiley +1 more source

