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Neurons

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Improving the Classification Performance of Dendrite Morphological Neurons.

IEEE transactions on neural networks and learning systems
Dendrite morphological neurons (DMNs) are neural models for pattern classification, where dendrites are represented by a geometric shape enclosing patterns of the same class. This study evaluates the impact of three dendrite geometries-namely, box, e...

Periodic solutions in next generation neural field models.

Biological cybernetics
We consider a next generation neural field model which describes the dynamics of a network of theta neurons on a ring. For some parameters the network supports stable time-periodic solutions. Using the fact that the dynamics at each spatial location ...

Jump-GRS: a multi-phase approach to structured pruning of neural networks for neural decoding.

Journal of neural engineering
Neural decoding, an important area of neural engineering, helps to link neural activity to behavior. Deep neural networks (DNNs), which are becoming increasingly popular in many application fields of machine learning, show promising performance in ne...

Comparison of visual quantities in untrained neural networks.

Cell reports
The ability to compare quantities of visual objects with two distinct measures, proportion and difference, is observed even in newborn animals. However, how this function originates in the brain, even before visual experience, remains unknown. Here, ...

Attention-based deep learning framework to recognize diabetes disease from cellular retinal images.

Biochemistry and cell biology = Biochimie et biologie cellulaire
A medical disorder known as diabetic retinopathy (DR) affects people who suffer from diabetes. Many people are visually impaired due to DR. Primary cause of DR in patients is high blood sugar, and it affects blood vessels available in the retinal cel...

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), ...