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I am trying to learn how to manipulate McCulloch-Pitts neurons in order to determine their weights and bias based off of inputs. In this example I have inputs:

x, y, z ∈ {−1,1}

The neuron's output is z if x = -1 and y = 1, and is -1 otherwise.

How do I compute the weights and bias for the neuron? An example or link to an example would be greatly appreciated. (Having a hard time finding examples online). Thanks!

So far I have been using the equation out = sgn((w1)(in1) + (w2)(in2) + (w3)(in3) - theta), but I am unsure whether or not I am taking the correct initial steps to solving this problem.

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The weights and bias for a given neuron depend on the task you are trying to solve. Each computation will have a different set of weights that will implement it.

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  • $\begingroup$ Does the method for finding those weights (which I think the question is asking for) also vary by task? Why? $\endgroup$ – Christian Hummeluhr May 15 '15 at 7:35

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