Results 41 to 50 of about 79,596 (285)

CoCalc as a Learning Tool for Neural Network Simulation in the Special Course "Foundations of Mathematic Informatics"

, 2018
The role of neural network modeling in the learning content of the special course "Foundations of Mathematical Informatics" was discussed. The course was developed for the students of technical universities - future IT-specialists and directed to ...
Markova, Oksana, Popel, Maiia, Semerikov, Serhiy   +2 more
core   +1 more source

Spin-Based Neuron Model with Domain Wall Magnets as Synapse

, 2012
We present artificial neural network design using spin devices that achieves ultra low voltage operation, low power consumption, high speed, and high integration density.
Augustine, Charles, Panagopoulos, Georgios, Roy, Kaushik, Sharad, Mrigank   +3 more
core   +1 more source

Time after time – circadian clocks through the lens of oscillator theory

FEBS Letters, EarlyView.
Oscillator theory bridges physics and circadian biology. Damped oscillators require external drivers, while limit cycles emerge from delayed feedback and nonlinearities. Coupling enables tissue‐level coherence, and entrainment aligns internal clocks with environmental cues.
Marta del Olmo, Carolin Ector, Hanspeter Herzel   +2 more
wiley   +1 more source

Interpreting high levels of unfolded Von Willebrand Factor in patients with the antiphospholipid syndrome

Frontiers in Immunology
IntroductionUnfolded Von Willebrand Factor (VWF) is increased in thrombotic pathologies such as myocardial infarction. Unfolded VWF mediates the binding of platelets without the need for collagen.
Romy de Laat-Kremers, Shengshi Huang, Shengshi Huang, Hugo ten Cate, Hugo ten Cate, Marisa Ninivaggi, Bas de Laat, Bas de Laat, Katrien Devreese, Katrien Devreese   +9 more
doaj   +1 more source

Memristor bridge synapse for better artificial neuron perceptron

AIP Advances, 2023
In artificial neural networks, the fourth passive element memristor can be utilized as an electronic synapse that serves as the interface between neurons.
Nuo Wang, Lei Li, Yulong Chen, Hongyu Wang, Zheming Yang, Dingyu Long   +5 more
doaj   +1 more source

Potential therapeutic targeting of BKCa channels in glioblastoma treatment

Molecular Oncology, EarlyView.
This review summarizes current insights into the role of BKCa and mitoBKCa channels in glioblastoma biology, their potential classification as oncochannels, and the emerging pharmacological strategies targeting these channels, emphasizing the translational challenges in developing BKCa‐directed therapies for glioblastoma treatment.
Kamila Maliszewska‐Olejniczak, Karolina Pytlak, Sandra Jaworowska, Bogusz Kulawiak, Piotr Bednarczyk   +4 more
wiley   +1 more source

Substrate-morphology driven tunable nanoscale artificial synapse

Journal of Asian Ceramic Societies, 2021
Two-terminal memristive devices are considering as a potential candidate to mimic human brain functionality to enable artificial intelligence. Particularly, two-terminal nanoscale devices are regarded as a promising solution for implementing bio-synapses
Shahid Iqbal, Mohit Kumar, Ranveer Singh, Qadeer Akbar Sial, Hyungtak Seo   +4 more
doaj   +1 more source

NOR-Type 3-D Synapse Array Architecture Based on Charge-Trap Flash Memory

IEEE Journal of the Electron Devices Society, 2022
In this work, we proposed a three-dimensional (3-D) channel stacked array architecture based on charge-trap flash (CTF) memory for an artificial neural network accelerator.
Jung Nam Kim, Jaehong Lee, Jo Eun Kim, Suck Won Hong, Minsuk Koo, Yoon Kim   +5 more
doaj   +1 more source

Neuronal synchrony: peculiarity and generality [PDF]

, 2008
Synchronization in neuronal systems is a new and intriguing application of dynamical systems theory. Why are neuronal systems different as a subject for synchronization?
Bell C. C., Bi G., der Malsburg C. V., Hodgkin A. L., Legendy C., Mikhail I. Rabinovich, Nowotny T., Rall W., Ramon Huerta, Sharp A. A., Szücs A., Thomas Nowotny, von der Malsburg C.   +12 more
core   +2 more sources

All‐in‐One Analog AI Hardware: On‐Chip Training and Inference with Conductive‐Metal‐Oxide/HfOx ReRAM Devices

Advanced Functional Materials, EarlyView.
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone, Victoria Clerico, Wooseok Choi, Tommaso Stecconi, Folkert Horst, Laura Bégon‐Lours, Matteo Galetta, Antonio La Porta, Nikhil Garg, Fabien Alibart, Bert Jan Offrein, Valeria Bragaglia   +11 more
wiley   +1 more source