AIMC Topic: Neurons

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A Cost-Efficient High-Speed VLSI Architecture for Spiking Convolutional Neural Network Inference Using Time-Step Binary Spike Maps.

Sensors (Basel, Switzerland) Sep 8, 2021
Neuromorphic hardware systems have been gaining ever-increasing focus in many embedded applications as they use a brain-inspired, energy-efficient spiking neural network (SNN) model that closely mimics the human cortex mechanism by communicating and ...
Neurons Recognition, Psychology Humans Neural Networks, Computer Computers Brain
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NeuriteNet: A convolutional neural network for assessing morphological parameters of neurite growth.

Journal of neuroscience methods Sep 2, 2021
BACKGROUND: During development or regeneration, neurons extend processes (i.e., neurites) via mechanisms that can be readily analyzed in culture. However, defining the impact of a drug or genetic manipulation on such mechanisms can be challenging due...
Neural Networks, Computer Animals Neurites Neurogenesis Mice Neurons
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Adaptive Dropout Method Based on Biological Principles.

IEEE transactions on neural networks and learning systems Aug 31, 2021
Dropout is one of the most widely used methods to avoid overfitting neural networks. However, it rigidly and randomly activates neurons according to a fixed probability, which is not consistent with the activation mode of neurons in the human cerebra...
Neural Networks, Computer Algorithms Humans Neurons Cerebral Cortex Deep Learning Models, Neurological
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Deep neural networks using a single neuron: folded-in-time architecture using feedback-modulated delay loops.

Nature communications Aug 27, 2021
Deep neural networks are among the most widely applied machine learning tools showing outstanding performance in a broad range of tasks. We present a method for folding a deep neural network of arbitrary size into a single neuron with multiple time-d...
Machine Learning Single-Cell Analysis Humans Neural Networks, Computer Neurons
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Impedance Spectroscopy Dynamics of Biological Neural Elements: From Memristors to Neurons and Synapses.

The journal of physical chemistry. B Aug 26, 2021
Understanding the operation of neurons and synapses is essential to reproducing biological computation. Building artificial neuromorphic networks opens the door to a new generation of faster and low-energy-consuming electronic circuits for computatio...
Electronics Synapses Dielectric Spectroscopy Neural Networks, Computer Neurons
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Universal Nonlinear Spiking Neural P Systems with Delays and Weights on Synapses.

Computational intelligence and neuroscience Aug 25, 2021
The nonlinear spiking neural P systems (NSNP systems) are new types of computation models, in which the state of neurons is represented by real numbers, and nonlinear spiking rules handle the neuron's firing. In this work, in order to improve computi...
Neurons Models, Neurological Synapses Action Potentials Neural Networks, Computer
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Constrained plasticity reserve as a natural way to control frequency and weights in spiking neural networks.

Neural networks : the official journal of the International Neural Network Society Aug 19, 2021
Biological neurons have adaptive nature and perform complex computations involving the filtering of redundant information. However, most common neural cell models, including biologically plausible, such as Hodgkin-Huxley or Izhikevich, do not possess...
Action Potentials Neurons Neural Networks, Computer Neuronal Plasticity Algorithms Models, Neurological
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No Fine-Tuning, No Cry: Robust SVD for Compressing Deep Networks.

Sensors (Basel, Switzerland) Aug 19, 2021
A common technique for compressing a neural network is to compute the -rank ℓ2 approximation Ak of the matrix A∈Rn×d via SVD that corresponds to a fully connected layer (or embedding layer). Here, is the number of input neurons in the layer, is the...
Data Compression Algorithms Neurons Neural Networks, Computer
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Stochastic Memristive Interface for Neural Signal Processing.

Sensors (Basel, Switzerland) Aug 19, 2021
We propose a memristive interface consisting of two FitzHugh-Nagumo electronic neurons connected via a metal-oxide (Au/Zr/ZrO(Y)/TiN/Ti) memristive synaptic device. We create a hardware-software complex based on a commercial data acquisition system, ...
Neural Networks, Computer Computers Signal Processing, Computer-Assisted Neurons Electronics
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A strategy for mapping biophysical to abstract neuronal network models applied to primary visual cortex.

PLoS computational biology Aug 16, 2021
A fundamental challenge for the theoretical study of neuronal networks is to make the link between complex biophysical models based directly on experimental data, to progressively simpler mathematical models that allow the derivation of general opera...
Nerve Net Visual Cortex Synapses Biophysical Phenomena Electrophysiological Phenomena Models, Neurological Brain Mapping Animals Kinetics Humans Neural Networks, Computer Computational Biology Neurons Computer Simulation
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