Federal gosudarstvennoe uchebnoe predpriyatie Chair of the System of Artificial Intelligence

Sloisto-polnosvyaznÿe seti sostoyat iz sloev, kajdyy iz kotoryx, v
polnosvyaznÿe.
Polnosvyazno-sloistye seti po svoey strukture takie je, no
seti.
i peredachi sleduyushchemu: na kajdom takte neyrony vsex sloev prinimayut
voznikaet togda, kogda chislo taktov funktsionirovaniya zaranee ne
funktsionirovanii signals peredayutsya ot sloya k sloyu i proisxodit exchange
svoyu ochered, predstavlyaet soboy polnosvyaznuyu set. Pri
Sushchestvennoe razlichie mezhdu polnosvyaznoy i sloistoy setyami
funktsioniruyut po-drugomu. V nix ne razdelyayutsya fazy obmena vnutri sloya
obrazom: priem signalov s predydushchego sloya (i / ili vxodnyx) ÿ exchange
- posledniy (k-y) peredaet svoi vyxodnÿe signalaly pervomu (risunok 1.10). Vse sloi ravnopravny i
mogut kak poluchat vxodnÿe signalaly, tak i
signalami vnutri sloya ÿ peredacha posleduyushchemu sloyu (ili na vyxod).
peredayut signal kak vnutri sloya, tak i posleduyushchemu (ili na vyxod). Do
ogranicheno - sloistaya set tak rabotat ne mojet.
Sloisto-tsiklicheskie sets otlichayutsya tem, chto sloi zamknutÿ v koltso
signalami vnutri sloya. V kajdom sloe etot protsess protekaet sleduyushchim
signaly ot neyronov kak svoego sloya, tak i predydushchego, posle chego
neogranichenno dolgo - so it is, as in polnosvyaznÿe.
chislo taktov, sootvetstvuyushchee kolichestvu sloev - tak je, kak i sloistye
polucheniya otveta takie seti mogut funktsionirovat dolgo - tak je, kak i
Podobnÿe seti to polucheniya otveta funktsioniruyut opredelennoe
Rice. 10. Sloisto-tsiklicheskaya set
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podayutsya on special input elements (for standard neurons - on
adaptivnyx summatorov) prisvaivayutsya znacheniya, ravnye vxodnÿm
sootvetstvuyushchie vesa;
variantov podachi vxodnyx signalov seti: 1) odin signal
- odin neyron - vxodnÿe signalaly podayutsya srazu na
Obÿchnÿy sposob snyatiya vyxodnyx signalov sostoit v tom, chto
schitayutsya ustanovivshiesya znacheniya vÿdelennyx parameters
In the last sluchae process funktsyonirovaniya dolzhen vklyuchat
ispolzuyutsya tolko dlya obmena signalami mejdu neuronami;
opredelennÿe momentu vremeni schitayutsya vyxodnymi signalami seti. Tolko eto i vÿdelyaet ix iz
vsego nabora neyronov.
signalami;
signals:
sootvetstvuet, skoree, obucheniyu. Funktsionirovanie with change
proxodyashchie po vÿdelennÿm svyazyam, uje umnojennÿe na
Obÿchnÿy sposob podachi vxodnyx signalov sostoit v tom, chto oni
(obÿchno sinapticheskim vesam - nekotorÿm parametram vÿdelennyx
dannom type vxodnyx signals.
spetsialnye vxodnye summatory). Sushchestvuet, odnako, i neskolko drugix
signalam.
2) parametric snyatie output - output signals
(naprimer, vesa vydelennyx svyazey).
nelineynye preobrazovateli, minuya summatory, kotorye
nekotorÿe neyronÿ obÿyavlyayutsya vyxodnymi i ix vyxodnÿe signalaly v
2) podacha na te je summatory, kotorye slujat dlya obmena
Sushchestvuet takje neskolko dopolnitelnyx variantov snyatiya
change of external synapses. In obÿchnoy stanovdake task this
3) parametricheskaya podacha - vÿdelennomu array of parameters
Inputs and outputs
1) additivnoe snyatie s synapsov - na vyxod podayutsya signalaly,
parameters mojno rassmatrivat kak obuchenie so vspomogatelnoy otsenkoy, parameters kotoroy
yavlyayutsya podstraivaemymi v xode «nastoyashchego» obucheniya, ustanavlivayushchego pravilnoe
sootvetstvie vxod-vyxod pri
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2
Znakovaya
Hyperbolicheskiy
6
Sigmoidnaya
or
(gaussova)
Function
3
nasyshcheniem
Sigmoidnaya or
Functions of neuronal activation.
Polulineynaya s
(sigmoid)
Treugolnaya
4 Polulineynaya
1 Porogovaya
5 Lineynaya
nasyshcheniem
Graphic
Title
sigmoidal
Lineynaya
tangent
signaturnaya
bazisnaya
s
Radial
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togda kak bipolyarnaya funktsiya mojet byt zadana v vide
function (t.e. function, the graph of which is similar to the letter "S"). On practice
Graph unipolar sigmoidal function
ravnym 1.
In kachestve funktsii aktivatsii chasto vÿstupaet sigmoidalnaya
razrabotchikom seti. Na praktike b dlya uproshcheniya naznachayut obÿchno