Recent advances and future prospects for memristive materials, devices, and systems
Memristive technology has been rapidly emerging as a potential alternative to traditional
CMOS technology, which is facing fundamental limitations in its development. Since oxide …
CMOS technology, which is facing fundamental limitations in its development. Since oxide …
Nonlinearity in memristors for neuromorphic dynamic systems
K Yang, J Joshua Yang, R Huang, Y Yang - Small Science, 2022 - Wiley Online Library
As semiconductor technology enters the more than Moore era, there exists an apparent
contradiction between the rapidly growing demands for data processing and the visible …
contradiction between the rapidly growing demands for data processing and the visible …
Spiking neurons with spatiotemporal dynamics and gain modulation for monolithically integrated memristive neural networks
As a key building block of biological cortex, neurons are powerful information processing
units and can achieve highly complex nonlinear computations even in individual cells …
units and can achieve highly complex nonlinear computations even in individual cells …
Power-efficient neural network with artificial dendrites
In the nervous system, dendrites, branches of neurons that transmit signals between
synapses and soma, play a critical role in processing functions, such as nonlinear …
synapses and soma, play a critical role in processing functions, such as nonlinear …
Neuromorphic device architectures with global connectivity through electrolyte gating
Abstract Information processing in the brain takes place in a network of neurons that are
connected with each other by an immense number of synapses. At the same time, neurons …
connected with each other by an immense number of synapses. At the same time, neurons …
Spike-timing-dependent plasticity learning of coincidence detection with passively integrated memristive circuits
Spiking neural networks, the most realistic artificial representation of biological nervous
systems, are promising due to their inherent local training rules that enable low-overhead …
systems, are promising due to their inherent local training rules that enable low-overhead …
Low‐Voltage, Optoelectronic CH3NH3PbI3−xClx Memory with Integrated Sensing and Logic Operations
Nonvolatile optoelectronic memories integrated with the functions of sensing, data storage,
and data processing are promising for the potential Internet of things (IoT) applications. To …
and data processing are promising for the potential Internet of things (IoT) applications. To …
Dendritic computation
One of the central questions in neuroscience is how particular tasks, or computations, are
implemented by neural networks to generate behavior. The prevailing view has been that …
implemented by neural networks to generate behavior. The prevailing view has been that …
Correlated neuronal activity and the flow of neural information
E Salinas, TJ Sejnowski - Nature reviews neuroscience, 2001 - nature.com
For years we have known that cortical neurons collectively have synchronous or oscillatory
patterns of activity, the frequencies and temporal dynamics of which are associated with …
patterns of activity, the frequencies and temporal dynamics of which are associated with …
[图书][B] Principles of computational modelling in neuroscience
D Sterratt, B Graham, A Gillies, G Einevoll, D Willshaw - 2023 - books.google.com
Taking a step-by-step approach to modelling neurons and neural circuitry, this textbook
teaches students how to use computational techniques to understand the nervous system at …
teaches students how to use computational techniques to understand the nervous system at …