1. Method for encoding an input pattern using a normalizer and a classifier during the learning phase, said input pattern being characterized by an essential feature or shape and at least one main parameter wherein said main parameter is an element susceptible of modifying the input pattern but not the shape, comprising the steps of: establishing a reference value for that main parameter; applying said input pattern to a normalizer that computes a main factor which measures the difference between the main parameter value of said input pattern and said reference value and that sets the input pattern at said reference value as a normalized pattern using said main factor; applying said normalized pattern and the category associated thereto by the user to a classifier; and, storing the normalized pattern in the classifier as a prototype; wherein said normalized pattern, said category and main factor represent the encoded pattern.