A technique which can be applied to any minimisation or

learning process based on successive update steps (either

random or deterministic) where the update step length is

proportional to an arbitrarily set parameter which can play

the role of a temperature. Then, in analogy with the

annealing of metals, the temperature is made high in the early

stages of the process for faster minimisation or learning,

then is reduced for greater stability.