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[‚self ‚ȯr·gə·nə′zā·shən]
The capability of a system to spontaneously generate a well-defined supramolecular entity by self-assembling from components in a given set of conditions.



a process during which the organization of a complex dynamic system is created, reproduced, or improved. Self-organization processes can occur only in systems that have a high level of complexity and a large number of elements; the relations between the elements must be of a probabilistic rather than a rigid nature. The properties of self-organization are exhibited by such diverse systems as a living cell, an organism, a biological population, a biocenosis, and a human community. The processes of self-organization involve the reorganization of existing relations between elements of the system and the formation of new relations. It is characteristic of self-organization processes that such processes are goal-oriented but, at the same time, natural and spontaneous. These processes may occur when the system interacts with the environment, but they are to some degree autonomous and are relatively independent of the environment.

Three types of processes of self-organization are distinguished. The first type is the self-generation of organization, that is, the emergence of a new, integral system with its own specific regularities from some aggregation of integral objects of a given level. An example is the genesis of multicellular organisms from unicellular ones. The second type comprises processes by which a system maintains a certain level of organization when changes occur in the external and internal conditions under which the system functions. The chief object of study here is homeostatic mechanisms (see HOMEOSTASIS), in particular, mechanisms whose operation is based on the negative-feedback principle. The third type involves the improvement and self-development of systems that are able to accumulate and make use of experience.

The problems of self-organization were first subjected to special investigation in cybernetics. The term “self-organizing system” was introduced by the English cyberneticist W. R. Ashby in 1947. Extensive study of self-organization began in the late 1950’s for the purpose of discovering new principles permitting the construction of equipment with a high level of reliability and the designing of computers capable of modeling various aspects of human mental activity. The investigation of the problems of self-organization has become one of the chief ways in which the ideas and methods of cybernetics, information theory, and systems theory enter biological and social knowledge.


Braines, S. N., and A. V. Napalkov. “Nekotorye voprosy teorii samoor-ganizuiushchikhsia sistem.” Voprosyfilosofii, 1959, no. 6.
Samoorganizuiushchiesia sistemy. Moscow, 1964. (Translated from English.)
Printsipy samoorganizatsii. Moscow, 1966. (Translated from English.)
Kremianskii, V. I. Strukturnye urovni zhivoi materii. Moscow, 1969.
Prigozhin, A. I. Sotsiologicheskie aspekty upravleniia. Moscow, 1974.
Self-organizing Systems. Washington, 1962.
Form by, J. An Introduction to the Mathematical Formulation of Self-organizing Systems. London, 1965.


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U-matrix representation of the Self-Organizing Map visualizes the distances between the neurons.
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The Self-Organizing Feature Maps are most simple to implement and hence a well known algorithm for compression of images.
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For solving our problem the self-organizing neural networks, whose structure and functioning are most related to real biological neural networks out of all types of artificial neural networks (Karayiannis 2004; Seiffert 2002; Marques de Sa 2001) were used.
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What better way to explore complexity in communication than to use an inherently complex and self-organizing system, an electronic online forum.
It's what I would call a self-organizing tendency of laser [light] and plasma to produce the effect we want," Tajima says.
Prigogine and Stengers 176) Thus, Prigogine sees complex, self-organizing subsystems as a logical consequence when chance and necessity function complementarily, not antagonistically.
A global assessment of the Self-Organizing Network (SON) software market, providing in-depth insight into the market drivers, barriers, vendor strategies and future prospects for the industry.
com/research/8fx2wf/analysis_of_the) has announced the addition of the "Analysis of the Global Self-Organizing Network (SON)Testing and Monitoring Equipment Market" report to their offering.
The reason is that the biological brain is configured differently and the key is its evolving structure, where connectivity elements between individual neurons, the synapses, undergo ~birth~ and ~death~ as well as strengthening and weakening through a selection process, reconfiguring neuronal connectivity in a self-organizing manner and allowing the networked population of neuronal processors to adapt motor and behavioural responses to the ever changing environment.

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