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Holographic models of information processing in neuron networks. (English. Russian original) Zbl 0789.92004
Sov. Phys., Dokl. 37, No. 5, 221-223 (1992); translation from Dokl. Akad. Nauk, Ross. Akad. Nauk 324, No. 3, 537-540 (1992).
The past decade has seen a revival of interest in neuron-like structures, in which information processes are realized through the parallel operation of a large number of elements. The results of these operations are manifested in a distributed fashion, in the form of global states of the network. An important distinction between contemporary approaches and the models of uniform structures which were popular in the 1960s, consisting of lattices of identical finite automata, is that attempts are now being made to characterize the states of neurons and of neuron networks by means of not only discrete logical parameters but also continuous pseudophysical parameters. In particular, active research is being carried out on a connectionist model, in which the information process is represented as a search for stable energy states of the network. In the present paper we propose a holographic approach to the modeling of information processes in neuron networks.
92B20 Neural networks for/in biological studies, artificial life and related topics
68T05 Learning and adaptive systems in artificial intelligence
94C99 Circuits, networks