AIMC Topic: Synapses

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Self-organization of an inhomogeneous memristive hardware for sequence learning.

Nature communications Oct 2, 2022
Learning is a fundamental component of creating intelligent machines. Biological intelligence orchestrates synaptic and neuronal learning at multiple time scales to self-organize populations of neurons for solving complex tasks. Inspired by this, we ...
Neural Networks, Computer Neurons Synapses Learning Algorithms
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ConvWin-UNet: UNet-like hierarchical vision Transformer combined with convolution for medical image segmentation.

Mathematical biosciences and engineering : MBE Sep 29, 2022
Convolutional Neural Network (CNN) plays a vital role in the development of computer vision applications. The depth neural network composed of U-shaped structures and jump connections is widely used in various medical image tasks. Recently, based on ...
Image Processing, Computer-Assisted Electric Power Supplies Synapses Neural Networks, Computer
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Optimal Mapping of Spiking Neural Network to Neuromorphic Hardware for Edge-AI.

Sensors (Basel, Switzerland) Sep 24, 2022
Neuromorphic hardware, the new generation of non-von Neumann computing system, implements spiking neurons and synapses to spiking neural network (SNN)-based applications. The energy-efficient property makes the neuromorphic hardware suitable for powe...
Computers Action Potentials Neural Networks, Computer Synapses Neurons
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Biopolymer based artificial synapses enable linear conductance tuning and low-power for neuromorphic computing.

Nanoscale Sep 15, 2022
Neuromorphic computing is considered a promising method for resolving the traditional von Neumann bottleneck. Natural biomaterial-based artificial synapses are popular units for constructing neuromorphic computing systems while suffering from poor li...
Biopolymers Carrageenan Neural Networks, Computer Synapses Biocompatible Materials
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Continuous learning of spiking networks trained with local rules.

Neural networks : the official journal of the International Neural Network Society Sep 7, 2022
Artificial neural networks (ANNs) experience catastrophic forgetting (CF) during sequential learning. In contrast, the brain can learn continuously without any signs of catastrophic forgetting. Spiking neural networks (SNNs) are the next generation o...
Neural Networks, Computer Brain Synapses Education, Continuing Neuronal Plasticity
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Dynamic branching in a neural network model for probabilistic prediction of sequences.

Journal of computational neuroscience Aug 10, 2022
An important function of the brain is to predict which stimulus is likely to occur based on the perceived cues. The present research studied the branching behavior of a computational network model of populations of excitatory and inhibitory neurons, ...
Neural Inhibition Neural Networks, Computer Neurons Synapses Models, Neurological
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Synergy of Spin-Orbit Torque and Built-In Field in Magnetic Tunnel Junctions with Tilted Magnetic Anisotropy: Toward Tunable and Reliable Spintronic Neurons.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Aug 4, 2022
Owing to programmable nonlinear dynamics, magnetic domain wall (DW)-based devices can be configured to function as spintronic neurons, promising to execute sophisticated tasks as a human brain. Developing energy-efficient, CMOS compatible, reliable, ...
Neural Networks, Computer Anisotropy Neurons Humans Synapses Torque Magnetic Phenomena
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Controlled Growth of Wafer-Scale Transition Metal Dichalcogenides with a Vertical Composition Gradient for Artificial Synapses with High Linearity.

ACS nano Aug 1, 2022
Artificial synapses are promising for dealing with large amounts of data computing. Great progress has been made recently in terms of improving the on/off current ratio, the number of states, and the energy efficiency of synapse devices. However, the...
Transition Elements Electric Conductivity Synapses Neural Networks, Computer
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Multi-Stimuli-Responsive Synapse Based on Vertical van der Waals Heterostructures.

ACS applied materials & interfaces Jul 26, 2022
Brain-inspired intelligent systems demand diverse neuromorphic devices beyond simple functionalities. Merging biomimetic sensing with weight-updating capabilities in artificial synaptic devices represents one of the key research focuses. Here, we rep...
Biomimetics Learning Neural Networks, Computer Synapses Neuronal Plasticity
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On Spiking Neural Membrane Systems with Neuron and Synapse Creation.

International journal of neural systems Jul 12, 2022
Spiking neural membrane systems are models of computation inspired by the natural functioning of the brain using the concepts of neurons and synapses, and represent a way of building computational systems of a biological inspiration. A variant of suc...
Models, Neurological Synapses Action Potentials Neural Networks, Computer Brain Neurons
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