To develop efficient storage as pseudo life by dynamically varying storage capacity in dependence on the degree of growth of the life, the reliability of information and the like.

In an associative storage system to which a competitive neural network is applied, a variation in a learning rate α controls storage capacity. The learning rate is handled, for example, as a function variable with growth time (t), so that storage capacity is varied dynamically according to the process of growth. A larger difference between a competitive neuron value yi winning a competition and other output neurons yk offers higher reliability of storage, and thus the learning rate α is varied according to reliability to develop efficient storage.