THE USAGE OF SIT-ELEMENTS FOR NETWORKS - Danilishyn , Illia; Danilishyn , Oleksandr; Pasynkov , V. (Collection of scientific papers «ΛΌГOΣ», 2023)
The all-encompassing monograph of Galushkin A.[1] embraces all aspects of networks but usual traditional approaches to networks are through classical mathematics, in particular through usual conformity operators. Here consider another approach – through new mathematics partition with containment operators, which though may be interpreted as a result of some conformity operators, but themselves are no conformity operators. The containment operators are more convenient for networks. Also main lay stress on the processors use, which work with triodes use, that does not use in Sit-networks in mainly. Sit-networks is represented by Sit-structure, which may constructed for necessary weights. Sit-OS (Sit operating system) are used Sit-coding and Sit-translation. In the first the coding is realized through 2-measured matrix –row (a,b), where the number b – the code of the action, the number a- the object code of this action. Sit-coding (or Self-coding) is realized through the matrix, which has 2 columns (in continuous case- 2 numbers intervals). Here initial coding is used for all matrix rows simultaneously. Sit-translation is realized by the inversion. In this case self-coding and Self-translation will be more stable in particular. The target weights fi in are chosen for necessary tasks. We will touch no questions of the applications, optimization of networks. They are detailed by Galushkin A.[1]. We touch difference of it for complex networks hierarchy only. The same simple executing programs are in the cores of simple artificial neurons of type Sit (designation - mnSt) for simple information processing. More complex executing programs are used for mnSt nodes. Unfortunately we change name St-elements [2] to Sit-elements because we find that St-elements were used by other authors early. Sit-threshold element –sgn( ), b- mnSt, x=(x1,x2,…,xn) – source signals values, a=(a1,a2,…,an) – Sit-synapses weights. The first level of mnSt consists from simple mnSt. The second level of mnSt consists from – Sit-node of mnSt in range D, D- holding capacity for mnSt node. The third level of mnSt consists from - Sit2- node of mnSt in range D, thus D becomes capacity in itself for mnSt. The usage of Sit2- nodes of mnSt is enough for our networks, but self level is more higher in living organisms, in particular Sitn-, n≥3. Target structure or corresponding eprogram by corresponding self-code enters to target block by means of alternating current. After that here takes place the activation of all networks or its part according to indicative target. May arise the opinion that we go out from networks ideology, but in fact networks presents complex hierarchy with capacity in itself of different levels in living organisms.