AIMC Topic: Neurons

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Learning smooth dendrite morphological neurons by stochastic gradient descent for pattern classification.

Neural networks : the official journal of the International Neural Network Society Sep 25, 2023
This article presents a learning algorithm for dendrite morphological neurons (DMN) based on stochastic gradient descent (SGD). In particular, we focus on a DMN topology that comprises spherical dendrites, smooth maximum activation function nodes, an...
Algorithms Random Forest Neural Networks, Computer Dendrites Neurons
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Pumping machine fault diagnosis based on fused RDC-RBF.

PloS one Sep 25, 2023
At present, the fault diagnosis of pumping units in major oil fields in China is time-consuming and inefficient, and there is no universal problem for high requirements of hardware resources. In this study, a fault fusion diagnosis method of pumping ...
Neural Networks, Computer Humans Algorithms Normal Distribution Cluster Analysis Neurons
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Brain-inspired neural circuit evolution for spiking neural networks.

Proceedings of the National Academy of Sciences of the United States of America Sep 20, 2023
In biological neural systems, different neurons are capable of self-organizing to form different neural circuits for achieving a variety of cognitive functions. However, the current design paradigm of spiking neural networks is based on structures de...
Algorithms Cell Communication Cognition Neural Networks, Computer Neurons
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Brain-guided manifold transferring to improve the performance of spiking neural networks in image classification.

Journal of computational neuroscience Sep 18, 2023
Spiking neural networks (SNNs), as the third generation of neural networks, are based on biological models of human brain neurons. In this work, a shallow SNN plays the role of an explicit image decoder in the image classification. An LSTM-based EEG ...
Models, Neurological Neurons Neural Networks, Computer Brain Humans
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A GPU-based computational framework that bridges neuron simulation and artificial intelligence.

Nature communications Sep 18, 2023
Biophysically detailed multi-compartment models are powerful tools to explore computational principles of the brain and also serve as a theoretical framework to generate algorithms for artificial intelligence (AI) systems. However, the expensive comp...
Brain Algorithms Neurons Humans Pyramidal Cells Artificial Intelligence
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Signatures of task learning in neural representations.

Current opinion in neurobiology Sep 12, 2023
While neural plasticity has long been studied as the basis of learning, the growth of large-scale neural recording techniques provides a unique opportunity to study how learning-induced activity changes are coordinated across neurons within the same ...
Neural Networks, Computer Neuronal Plasticity Neurons Learning
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An exact mapping from ReLU networks to spiking neural networks.

Neural networks : the official journal of the International Neural Network Society Sep 11, 2023
Deep spiking neural networks (SNNs) offer the promise of low-power artificial intelligence. However, training deep SNNs from scratch or converting deep artificial neural networks to SNNs without loss of performance has been a challenge. Here we propo...
Neurons Neural Networks, Computer Artificial Intelligence
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Learning heterogeneous delays in a layer of spiking neurons for fast motion detection.

Biological cybernetics Sep 11, 2023
The precise timing of spikes emitted by neurons plays a crucial role in shaping the response of efferent biological neurons. This temporal dimension of neural activity holds significant importance in understanding information processing in neurobiolo...
Neurons Action Potentials Neural Networks, Computer Learning Algorithms
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Predictive learning by a burst-dependent learning rule.

Neurobiology of learning and memory Sep 9, 2023
Humans and other animals are able to quickly generalize latent dynamics of spatiotemporal sequences, often from a minimal number of previous experiences. Additionally, internal representations of external stimuli must remain stable, even in the prese...
Humans Models, Neurological Neurons Animals Neural Networks, Computer
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Hybrid neuromorphic hardware with sparing 2D synapse and CMOS neuron for character recognition.

Science bulletin Sep 7, 2023
Neuromorphic computing enables efficient processing of data-intensive tasks, but requires numerous artificial synapses and neurons for certain functions, which leads to bulky systems and energy challenges. Achieving functionality with fewer synapses ...
Neurons Molybdenum Oxides Synapses Semiconductors Neural Networks, Computer
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