We study a population of interacting species, described by the replicator model well established in theoretical biology. Using methods of statistical physics we present an exact steady state solution to the model as a function of the population's cooperation pressure u when the number of species is large and the interactions are taken as random. When u is lowered to a critical value u c , the solution becomes unstable. This phase transition manifests itself by a 1/f behaviour in the powerspectrum of the system's response against weak external noise.

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Two simple storing prescriptions are presented for neural network models of TV two-state neurons. These rules are local and allow the embedding of correlated patterns without errors in a network of spin-glass type. Starting from an arbitrary configuration of synaptic bonds, up to TV patterns can be stored by successive modification of the synaptic efficacies. Proofs for the convergence are given. Extensions of these rules are possible.

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