neural network


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Related to neural network: Artificial neural network

neural network

also neural net
n.
A device or software program in which many interconnected elements process information simultaneously, adapting and learning from past patterns. Neural networks are often used to model the human brain.

neural network

n
1. (Physiology) an interconnected system of neurons, as in the brain or other parts of the nervous system
2. (Computer Science) Also called: neural net an analogous network of electronic components, esp one in a computer designed to mimic the operation of the human brain

neu′ral net′work


n.
1. any group of neurons that conduct impulses in a coordinated manner, as the assemblages of brain cells that record a visual stimulus.
2. Also called neu′ral net′. a computer model designed to simulate the behavior of biological neural networks, as in pattern recognition, language processing, and problem solving, with the goal of self-directed information processing.
[1985–90]
neural, neural network - Neural comes from Greek neuron, "nerve"; neural network can now refer to computer architecture in which processors are connected in a manner suggestive of connections between neurons.
See also related terms for network.
ThesaurusAntonymsRelated WordsSynonymsLegend:
Noun1.neural network - computer architecture in which processors are connected in a manner suggestive of connections between neurons; can learn by trial and error
computer architecture - the art of assembling logical elements into a computing device; the specification of the relation between parts of a computer system
2.neural network - any network of neurons or nuclei that function together to perform some function in the body
nervous system, systema nervosum - the sensory and control apparatus consisting of a network of nerve cells
reticulum - any fine network (especially one in the body composed of cells or blood vessels)
reticular formation, RF - a complex neural network in the central core of the brainstem; monitors the state of the body and functions in such processes as arousal and sleep and attention and muscle tone
RAS, reticular activating system - the network in the reticular formation that serves an alerting or arousal function
Translations
réseau neuronal

neural network

n (Anat) → Nervennetzwerk nt; (Comput) → neurales Netz
References in periodicals archive ?
This second stage is referred to as inference, and performing inference at the edge or natively inside the device brings numerous benefits in terms of latency, power consumption and privacy: Compile: Automatically convert a trained Caffe-based convolutional neural network (CNN) into an embedded neural network optimized to run on the onboard Movidius Myriad 2 VPU.
This technique can be applied with the help of neural network analysis or multilinear regression approach.
After training his neural network, he found that in just a few days, it was able to learn quickly, and managed to sort 4,000 pieces with a 90 percent accuracy rate.
RBF neural network refers to an artificial neural network, which exploits radial basis functions as activation functions.
Apple's move comes a few days after Google added support for iPhones and iPads to its TensorFlow neural network.
Multilayer Perceptron Networks (MLP Networks) and Radial Basis Function Networks (RBF networks) are the two popular methods of feed forward neural network.
i], which is also interpreted as a simple single- layer type of neural network [5].
Although the decision on the basis of neural network may look and behave like normal software, they are different in principle, since most implementations based on neural networks "learn" and not programmed: the network learns to perform the task, and is not programmed directly.
Su Peng from Harbin Institute of Technology created a recurrent neural network to solve the pseudo-convex optimization problem with linear equation constraint condition in the perspective of variational inequality in Research on Several Kinds of Nonlinear Optimization Problems Based on Neural Network [2].
These are in particular the automation of procedures which create, train and evaluate neural networks as well as providing all necessary interfaces between the control system and the operating system in which the trained neural network is embedded.
Among their topics are detecting defects in composite materials, using outlier analysis and multilayer perceptron neural networks to identify and localize damage in plastic composite plates reinforced with carbon fibers, predicting fatigue life, optimizing the neural network prediction of composite fatigue life under variable amplitude loading using Bayesian regularization, and determining initial design parameters by using genetically optimized neural network systems.
Neural network models with 10 parameters were trained by data of 14 projects and, were validated with 4 projects for predesign cost estimation of highway projects (Hegazy and Ayed 1998).

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