AIMC Topic: Neurons

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Sparser spiking activity can be better: Feature Refine-and-Mask spiking neural network for event-based visual recognition.

Neural networks : the official journal of the International Neural Network Society
Event-based visual, a new visual paradigm with bio-inspired dynamic perception and μs level temporal resolution, has prominent advantages in many specific visual scenarios and gained much research interest. Spiking neural network (SNN) is naturally s...

Reconfigurable neuromorphic computing block through integration of flash synapse arrays and super-steep neurons.

Science advances
Neuromorphic computing (NC) architecture inspired by biological nervous systems has been actively studied to overcome the limitations of conventional von Neumann architectures. In this work, we propose a reconfigurable NC block using a flash-type syn...

Multidirectional Associative Memory Neural Network Circuit Based on Memristor.

IEEE transactions on biomedical circuits and systems
Multidirectional associative memory neural network(MAMNN) is a direct extension of bidirectional associative memory neural network, which can handle multiple associations. In this work, a circuit of MAMNN based on memristor is proposed, which simulat...

The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory.

Neural networks : the official journal of the International Neural Network Society
Artificial Intelligence and Machine learning have been widely used in various fields of mathematical computing, physical modeling, computational science, communication science, and stochastic analysis. Approaches based on Deep Artificial Neural Netwo...

Optimization of neural-network model using a meta-heuristic algorithm for the estimation of dynamic Poisson's ratio of selected rock types.

Scientific reports
This research focuses on the predictive modeling between rocks' dynamic properties and the optimization of neural network models. For this purpose, the rocks' dynamic properties were measured in terms of quality factor (Q), resonance frequency (FR), ...

Intrinsic neural diversity quenches the dynamic volatility of neural networks.

Proceedings of the National Academy of Sciences of the United States of America
Heterogeneity is the norm in biology. The brain is no different: Neuronal cell types are myriad, reflected through their cellular morphology, type, excitability, connectivity motifs, and ion channel distributions. While this biophysical diversity enr...

Analysis on the inherent noise tolerance of feedforward network and one noise-resilient structure.

Neural networks : the official journal of the International Neural Network Society
In the past few decades, feedforward neural networks have gained much attraction in their hardware implementations. However, when we realize a neural network in analog circuits, the circuit-based model is sensitive to hardware nonidealities. The noni...

High-resolution CMOS-based biosensor for assessing hippocampal circuit dynamics in experience-dependent plasticity.

Biosensors & bioelectronics
Experiential richness creates tissue-level changes and synaptic plasticity as patterns emerge from rhythmic spatiotemporal activity of large interconnected neuronal assemblies. Despite numerous experimental and computational approaches at different s...

Model discovery to link neural activity to behavioral tasks.

eLife
Brains are not engineered solutions to a well-defined problem but arose through selective pressure acting on random variation. It is therefore unclear how well a model chosen by an experimenter can relate neural activity to experimental conditions. H...

Highly Bionic Neurotransmitter-Communicated Neurons Following Integrate-and-Fire Dynamics.

Nano letters
In biological neural networks, chemical communication follows the reversible integrate-and-fire (I&F) dynamics model, enabling efficient, anti-interference signal transport. However, existing artificial neurons fail to follow the I&F model in chemica...