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O que (quem) é artificial neural network - definição
Artificial neural network
.svg?width=200 "An ANN dependency graph")
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Artificial neural networks (ANNs), usually simply called neural networks (NNs) or neural nets, are computing systems inspired by the biological neural networks that constitute animal brains.
artificial neural network
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Neural net; Neural nets; Massive neural network; Neuralnets; Neuralnet; Artificial neural networs; Artificial neural networks; Artificial Neural Networks; Distributed representation; Nervous network; Nueral Network; Simulated neural network; Artificial Neural Network; Simulated Neural Network; Neural Network; Stochastic neural network; Present challenges in neural Networks; Problems in the verge of success in neural network research; Nervous Network; Bayesian neural network; Nueral networks; Neural network processor; Neural network processors; Neural computing; Neural circuitry; Neural Nets; Neural networks in robotics; Artificial neural net; Fuzzy neural networks; Neural network (computer); Neural network models; Neural network model; Models of neural network; Models of neural networks; Neural networks (computer); Aritificial Neuron Network; Computational network; History of Neural Networks; Convergent recursive learning algorithm; Deep stacking network; Tensor deep stacking network; Deep predictive coding networks; Applications of artificial neural networks; Neural network (artificial); Algorithms for training neural networks; Parameter (machine learning); Criticism of artificial neural networks; Self-learning in artificial neural network
<artificial intelligence> (ANN, commonly just "neural network"
or "neural net") A network of many very simple processors
("units" or "neurons"), each possibly having a (small amount
of) local memory. The units are connected by unidirectional
communication channels ("connections"), which carry numeric
(as opposed to symbolic) data. The units operate only on
their local data and on the inputs they receive via the
connections.
A neural network is a processing device, either an
algorithm, or actual hardware, whose design was inspired by
the design and functioning of animal brains and components
thereof.
Most neural networks have some sort of "training" rule whereby
the weights of connections are adjusted on the basis of
presented patterns. In other words, neural networks "learn"
from examples, just like children learn to recognise dogs from
examples of dogs, and exhibit some structural capability for
generalisation.
Neurons are often elementary non-linear signal processors (in
the limit they are simple threshold discriminators). Another
feature of NNs which distinguishes them from other computing
devices is a high degree of interconnection which allows a
high degree of parallelism. Further, there is no idle memory
containing data and programs, but rather each neuron is
pre-programmed and continuously active.
The term "neural net" should logically, but in common usage
never does, also include biological neural networks, whose
elementary structures are far more complicated than the
mathematical models used for ANNs.
See Aspirin, Hopfield network, McCulloch-Pitts neuron.
Usenet newsgroup: news:comp.ai.neural-nets.
(1997-10-13)
neural nets
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Exemplos do corpo de texto para artificial neural network
1. An artificial neural network could be made to switch on when it "sees" something it knows – a tortoise, say – and it will learn to associate a certain pattern of neuron activity with it.