The generalized preprocessing perceptron, ¹ as a function from ⁿ to R can be written as y = Φni=1φi(wi, gi (xi)) where xi are the inputs, gi is in the preprocessing layer, wi represents the uncertainty for the conclusion from xi to the output y, φi (wi, si) represents the semantics of implication xi →wi y, and Φ corresponds to a logical disjunction that calculates an incremence of evidence. Typically, Φ has a greater function, and is an assembly of co-t-norms.