The aim of this paper is to address the problem of weight storage at the end of the learning phase, an important problem encoun- tered in analog implementation of artificial neural networks. Circuits for weight storage must satisfy essentially two requirements: they must be as simple as possible and they must be able to maintain the informa- tion indefinitely. In this paper we suggest a multilevel (or quantised) weight storage approach which can be easily implemented by standard low complexity circuitry and neither requires refreshing nor conversion.
A Multistable Circuit for Weight Storage in Analog Artificial Neural Networks / Conti, Massimo; G., Guaitini; Orcioni, Simone; Turchetti, Claudio. - (1997), pp. 92-96.