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The idea of a computer which programs itself is very appealing.If Microsoft's Windows 2000 could reprogram itself, it might be able to repair the thousands of bugs that the programming staff made.While the system is as ancient as air traffic control systems, like air traffic control systems, it is still in commercial use.
There were a few advances in the field, but for the most part research was few and far between.
In 1972, Kohonen and Anderson developed a similar network independently of one another, which we will discuss more about later.
Applying this rule still results in an error if the line before the weight is 0, although this will eventually correct itself.
If the error is conserved so that all of it is distributed to all of the weights than the error is eliminated.
0 or 1) according to the rule: Weight Change = (Pre-Weight line value) * (Error / (Number of Inputs)).
Term Paper Neural Networks
It is based on the idea that while one active perceptron may have a big error, one can adjust the weight values to distribute it across the network, or at least to adjacent perceptrons.
Unfortunately for him, the first attempt to do so failed.
In 1959, Bernard Widrow and Marcian Hoff of Stanford developed models called "ADALINE" and "MADALINE." In a typical display of Stanford's love for acronymns, the names come from their use of Multiple ADAptive LINear Elements.
Such systems "learn" to perform tasks by considering examples, generally without being programmed with task-specific rules.
For example, in image recognition, they might learn to identify images that contain cats by analyzing example images that have been manually labeled as "cat" or "no cat" and using the results to identify cats in other images.