Multiple threshold perceptron

摘要

As a natural generalization of the linear perceptron with a single threshold element, we define a multiple threshold perceptron which learns a particular type of piecewise linear discriminant set of functions, namely those that are describable by a set of parallel hyperplanes. We also suggest a learning method in the form of an error-correction procedure, and a kind of gradient method that seeks the minimum of a rational criterion function. Experimental results show that the proposed procedure is effective.