AIMC Topic: Synapses

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Bioinspired and Low-Power 2D Machine Vision with Adaptive Machine Learning and Forgetting.

ACS nano Oct 28, 2022
Natural intelligence has many dimensions, with some of its most important manifestations being tied to learning about the environment and making behavioral changes. In primates, vision plays a critical role in learning. The underlying biological neur...
Neural Networks, Computer Artificial Intelligence Machine Learning Semiconductors Synapses
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The gate injection-based field-effect synapse transistor with linear conductance update for online training.

Nature communications Oct 28, 2022
Neuromorphic computing, an alternative for von Neumann architecture, requires synapse devices where the data can be stored and computed in the same place. The three-terminal synapse device is attractive for neuromorphic computing due to its high stab...
Neural Networks, Computer Synapses
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Complementary Memtransistor-Based Multilayer Neural Networks for Online Supervised Learning Through (Anti-)Spike-Timing-Dependent Plasticity.

IEEE transactions on neural networks and learning systems Oct 27, 2022
We propose a complete hardware-based architecture of multilayer neural networks (MNNs), including electronic synapses, neurons, and periphery circuitry to implement supervised learning (SL) algorithm of extended remote supervised method (ReSuMe). In ...
Neural Networks, Computer Neuronal Plasticity Models, Neurological Supervised Machine Learning Synapses
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Neuromorphic Liquids, Colloids, and Gels: A Review.

Chemphyschem : a European journal of chemical physics and physical chemistry Oct 20, 2022
Advances in flexible electronic devices and robotic software require that sensors and controllers be virtually devoid of traditional electronic components, be deformable and stretch-resistant. Liquid electronic devices that mimic biological synapses ...
Robotics Electronics Synapses Gels Colloids
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Enzymatic Numerical Spiking Neural Membrane Systems and their Application in Designing Membrane Controllers.

International journal of neural systems Oct 17, 2022
Spiking neural P systems (SN P systems), inspired by biological neurons, are introduced as symbolical neural-like computing models that encode information with multisets of symbolized spikes in neurons and process information by using spike-based rew...
Neural Networks, Computer Algorithms Fuzzy Logic Models, Neurological Action Potentials Neurons Synapses
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Two-dimensional materials-based probabilistic synapses and reconfigurable neurons for measuring inference uncertainty using Bayesian neural networks.

Nature communications Oct 17, 2022
Artificial neural networks have demonstrated superiority over traditional computing architectures in tasks such as pattern classification and learning. However, they do not measure uncertainty in predictions, and hence they can make wrong predictions...
Neural Networks, Computer Bayes Theorem Neurons Synapses Uncertainty
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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 Algorithms Learning Neurons Synapses
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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 ...
Neural Networks, Computer Image Processing, Computer-Assisted Synapses Electric Power Supplies
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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...
Neural Networks, Computer Computers Action Potentials Neurons Synapses
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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...
Neural Networks, Computer Biocompatible Materials Synapses Carrageenan Biopolymers
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