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Probably the simplest neural network design is the so-called
"percepton," which consists of one "trainable" artificial
neuron. Rather than being connected to other neurons, the
percepton is fed a series of weighted inputs. The percepton
can be trained, as described above, to solve very simple
problems by modifying the weights of the inputs. For a
more detailed discussion of the percepton, see http://dsl.serc.iisc.ernet.in/~vikram/nn_intro.html.
In the next article, we'll begin to look at some of the applications
of neural networks in the world of scientific computing.
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