Results 81 to 90 of about 31,264 (300)
A Biologically Inspired Sound Localisation System Using a Silicon Cochlea Pair
We present a biologically inspired sound localisation system for reverberant environments using the Cascade of Asymmetric Resonators with Fast-Acting Compression (CAR-FAC) cochlear model. The system exploits a CAR-FAC pair to pre-process binaural signals
Ying Xu +6 more
doaj +1 more source
Historical Foundation and Practical Guideline for Ferroelectric Switching Kinetic Studies
The P and U pulses in the conventional PUND measurements are not identical because of the interplay between switching current and the measurement circuit components. This circuit effect can lead to a shift in polarization transients and misinterpreted physics in the switching kinetics.
Yi Liang, Pat Kezer, John T. Heron
wiley +1 more source
Probabilistic metaplasticity for continual learning with memristors in spiking networks
Edge devices operating in dynamic environments critically need the ability to continually learn without catastrophic forgetting. The strict resource constraints in these devices pose a major challenge to achieve this, as continual learning entails memory
Fatima Tuz Zohora +3 more
doaj +1 more source
Transport characteristics and electrochemical properties of Y3+ doped Li4Ti5O12 as anode material
Li4Ti5-xYxO12 (x=0, 0.05, 0.10, 0.15, 0.20) anode materials were synthesized by ball milling assisted solid-state method used Li2CO3 and anatase TiO2 as raw materials and yttrium nitrate (Y(NO3)3·6H2O) as yttrium source.
WU Bing +7 more
doaj +1 more source
Monolithic UV‐ozone oxidation of Ta forms an ultrathin Ta2O5/TaOx bilayer enabling resistive switching with a vertical defect gradient. A stoichiometric surface layer over an oxygen‐deficient sublayer promotes localized filament nucleation near the top interface, enabling low‐voltage operation, and reduced cycle‐to‐cycle variability.
Seunghoon Yang +11 more
wiley +1 more source
Two-Dimensional Oscillatory Neural Networks for Energy Efficient Neuromorphic Computing
Neuro-inspired computing architectures are one of the leading candidates to solve complex and large-scale associative learning problems for AI applications. The two key building blocks for neuromorphic computing are the neuron and the synapse, which form
Linares-Barranco, Bernabé +19 more
core +5 more sources
Self-organized nanoscale networks: are neuromorphic properties conserved in realistic device geometries? [PDF]
Self-organised nanoscale networks are currently under investigation because of their potential to be used as novel neuromorphic computing systems. In these systems, electrical input and output signals will necessarily couple to the recurrent electrical ...
Acharya, S +7 more
core +1 more source
Nanoscale Spatial Tuning of Superconductivity in Cuprate Thin Films via Direct Laser Writing
Maskless direct laser writing enables local control of oxygen stoichiometry in epitaxial YBCO thin films under ambient conditions. Sub‐micrometer grayscale patterns with tunable optical response and superconducting transport properties are achieved.
Irene Biancardi +11 more
wiley +1 more source
2022 roadmap on neuromorphic computing and engineering [PDF]
Modern computation based on von Neumann architecture is now a mature cutting-edge science. In the von Neumann architecture, processing and memory units are implemented as separate blocks interchanging data intensively and continuously. This data transfer
Bartolozzi, Chiara +58 more
core +1 more source
Sodium alginate regulates interfacial ion transport and retention in electrolyte‐gated synaptic transistors. The carboxylate‐rich polymeric network forms a dynamic interfacial ion‐diffusion barrier that facilitates ion injection during programming while suppressing ion back‐diffusion, thereby stabilizing the electrochemically doped channel state.
Chaeyeon Han +6 more
wiley +1 more source

