How to compute weights and bias for a McCulloch-Pitts neuron? 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.
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.