Cybernetic Trading Strategies – Developing a Profitable Trading System with State-of-the-Art Technologies : [PDF Download]

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“A perceptron neural network learns by repeatedly producing an answer for each case, using the current value of its weights and comparing that value to the correct answer.

It then adjusts the weights to try to better learn the complete set of data. We call this process “supervised learning.” With simple two-layer perceptrons, the method or algorithm used to adjust these weights could not solve a very important type of problem.

In 1969, Minsky and Papart, in a book entitled The Perceptron, proved that a simple perceptron with two layers could not solve “non-linearly separable problems” such as “Exclusive OR.” An example of an Exclusive OR problem is: You can go to the store or to see a movie, but you cannot do both.”

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