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- W76432217 abstract "Beginning with the seminal work of McCulloch and Pitts in the early 1940s, the pursuit of increasingly accurate mathematical characterizations of the electrophysiological properties of individual neurons and networks of interconnected neurons has been a driving force in neural network research. This line of research has branched into descriptions of the nervous system at many different grains of analysis, including complex mathematical models of the properties of a single neuron, models of simple biological networks involving small numbers of neurons, and more abstract models which act as simplified treatments of large-scale networks involving millions of neurons in the nervous systems of humans and other vertebrates. At various points in the history of neural network research, successful neural network models have spread beyond the biological modeling domain into the domains of engineering and medical applications. Because they are capable of learning complicated nonlinear relationships from sets of training examples, neural networks are particularly well suited to pattern recognition problems involving the detection of complicated trends in high-dimensional datasets, such as the detection of medical abnormalities from physiological measures." @default.
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- W76432217 date "2001-01-01" @default.
- W76432217 modified "2023-09-27" @default.
- W76432217 title "Neural Networks: Biological Models and Applications" @default.
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- W76432217 doi "https://doi.org/10.1016/b0-08-043076-7/03667-6" @default.
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