Results 21 to 30 of about 1,932,979 (312)
Understanding the Impact of Neural Variations and Random Connections on Inference
Frontiers in Computational Neuroscience, 2021 Recent research suggests that in vitro neural networks created from dissociated neurons may be used for computing and performing machine learning tasks.
Yuan Zeng +10 more
doaj +1 more source
Artificial neural network in diagnostic cytology
CytoJournal, 2022 The artificial neural network (ANN) is a computer software design or model that simulates the biological neural network of the human brain. Instead of biological neurons, ANN is composed of many layers of nodes that carry the signal and process it to ...
P. Dey
semanticscholar +1 more source
Brain Sciences, 2020 Most existing cortico-hippocampal computational models use different artificial neural network topologies. These conventional approaches, which simulate various biological paradigms, can get slow training and inadequate conditioned responses for two ...
Mustafa Khalid +6 more
doaj +1 more source
Biologically informed deep neural network for prostate cancer discovery
Nature, 2021 The determination of molecular features that mediate clinically aggressive phenotypes in prostate cancer remains a major biological and clinical challenge1,2.
Haitham A. Elmarakeby +13 more
semanticscholar +1 more source
ACM SIGSPATIAL International Workshop on Advances in Geographic Information Systems, 2020 : An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the biological nervous systems, such as the brain, which process information.
Satchidananda Dehuri +2 more
semanticscholar +1 more source
Optimization Algorithm of Neural Network Structure Based on Adaptive Genetic Algorithm
Journal of Harbin University of Science and Technology, 2021 The structural design of neural network is one of the hot issues in neural network research The number of hidden layers and nodes has a great influence on the convergence speed and generalization ability of neural network Genetic algorithm is an adaptive
XILiang, WANGRui dong
doaj +1 more source
A biomimetic neural encoder for spiking neural network
Nature Communications, 2021 Spiking neural networks (SNNs) promise to bridge the gap between artificial neural networks (ANNs) and biological neural networks (BNNs) by exploiting biologically plausible neurons that offer faster inference, lower energy expenditure, and event-driven ...
Shiva Subbulakshmi Radhakrishnan +4 more
semanticscholar +1 more source
CMOS circuit implementations for neuron models [PDF]
, 1990 The mathematical neuron basic cells used as basic cells in popular neural network architectures and algorithms are discussed. The most popular neuron models (without training) used in neural network architectures and algorithms (NNA) are considered ...
Linares Barranco, Bernabé +2 more
core +1 more source
FitzHugh-Nagumo equations with generalized diffusive coupling
Mathematical Biosciences and Engineering, 2013 The aim of this work is to investigate the dynamics of a neural network, in which neurons, individually described by the FitzHugh-Nagumo model, are coupled by a generalized diffusive term.
Anna Cattani
doaj +1 more source
Deformation prediction programming based on MATLAB and BP neural network [PDF]
E3S Web of Conferences, 2022 In order to solve land tension problems, high-rise buildings become more and more common in the modern big cities. Meanwhile, it is necessary to monitor the deformation of the high-rise buildings for their safety. Based on the deformation monitoring data,
Zheng Haoxin, Chang Zhanqiang, Liu Jiaxi
doaj +1 more source