AIMC Topic: Synapses

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Deep learning-based synapse counting and synaptic ultrastructure analysis of electron microscopy images.

Journal of neuroscience methods Nov 19, 2022
BACKGROUND: Synapses are the connections between neurons in the central nervous system (CNS) or between neurons and other excitable cells in the peripheral nervous system (PNS), where electrical or chemical signals rapidly travel through one cell to ...
Deep Learning Neurons Synapses Microscopy, Electron Synaptic Vesicles
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Forgetting memristor based STDP learning circuit for neural networks.

Neural networks : the official journal of the International Neural Network Society Nov 19, 2022
The circuit implementation of STDP based on memristor is of great significance for the application of neural network. However, recent research shows that the research on the pure circuit implementation of forgetting memristor and STDP is still rare. ...
Neural Networks, Computer Learning Neuronal Plasticity Memory, Short-Term Synapses
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Compact artificial neuron based on anti-ferroelectric transistor.

Nature communications Nov 17, 2022
Neuromorphic machines are intriguing for building energy-efficient intelligent systems, where spiking neurons are pivotal components. Recently, memristive neurons with promising bio-plausibility have been developed, but with limited reliability, bulk...
Neural Networks, Computer Computers Reproducibility of Results Neurons Synapses
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An Electrochemical-Electret Coupled Organic Synapse with Single-Polarity Driven Reversible Facilitation-to-Depression Switching.

Advanced materials (Deerfield Beach, Fla.) Nov 2, 2022
Neuromorphic engineering and artificial intelligence demands hardware elements that emulates synapse algorithms. During the last decade electrolyte-gated organic conjugated materials have been explored as a platform for artificial synapses for neurom...
Neural Networks, Computer Artificial Intelligence Reproducibility of Results Depression 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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