resheniya prikladnyx zadach.
kontrolnyx rabot. V
xode izucheniya dannogo kursa student slushaet lektsii, poseshchaet
rabotÿ poiskovogo i obzornogo harakter, v tom chisle po materialam
NIRS, participation in scientific seminars and conferences, reception
predpolagaet, pomosho poseshcheniy lektsiy i seminararskix zanyatiy, vÿpolnenie
domashnix zadaniy. Osoboe mesto v ovladenii dannym kursom
razlichiem v spetsifike rabot studenty samostoyatelno vÿbirayut
subject. Ekzamenatsionnÿe trebovaniya svodyatsya k sleduyushchemu: student
As a result of studying the
disciplines of the student
must: 1) study the basic models of neurons and neural
networks; 2) znat osnovnye tipy modeley neyrokompyuternyx sistem i oblasti ix
zakrÿtymi options otvetov.
na samostoyatelnuyu rabotu ne vÿdaetsya po variantam, a vybiraetsya
aktivnogo podkhoda k izuchaemoy professii i znanie jelaemogo studentom
novoe, s obyazatelnÿm utverjdeniem prepodavatelem. Zadaniya mogut imet
The course zavershaetsya zachetom. Obyazatelnym usloviem dopuska studenta k
Tsel distsipliny - oznakomlenie studentov s novoy perspektivnoy
rabot. Krome togo, sposobstvuyut polucheniyu maksimalnoy
otsenki uchastie v
seminarskih i prakticheskix zanyatiy, vÿpolnenie laboratornyx i
apparatnoy i programmnoy rabot, takje mojet vklyuchat v sebya razlichnÿe
neyrokompyuterov, vozmojnostyami ispolzovaniya neyronnyx setey dlya
prakticheskie zanyatiya, zanimaetsya individno. Course development
Internet, in English, other works. V svyazi s bolshim
certificates on topics or specialties,
close to izuchaemomu
2. Trebovaniya k urovnyu osvoeniya soderjaniya discipline
doljen samostoyatelno otvetit na neskolko desyatkov voprosov s
otvoditsya samostoyatelnoy rabote. V svyazi s osobennostyami kursa, zadanie
napravlenie rabot i temu, chto trebuet, krome vsego prochego, nalichiya
application.
studentom from predvaritelnogo list vozmojnyx zadaniy ili predlagaetsya
vida deyatelnosti.
1.
Tseli i zadachi discipline
raznuyu napravlennost - bolee apparatnuyu, bolee programmnuyu, sochetanie
Programmoy kursa predusmotreno chtenie lektsiy, provedenie
ÿÿÿÿÿÿÿÿ yavlyaetsya vÿpolnenie i zashchita v techenie semester laboratornyx
oblast informatics, based on the principles of organization and work
5
Machine Translated by Google
i
ispolzovanii
pokazateley chuvstvitelnosti s pomoshchyu setey Koxonena i setey obratnogo
avtomatov. Neyronnye set obratnogo rasprostraneniya oshibki. Izbytochnost
INS; methods of optimizing the structure of the network.
commercial
neurocomputers; 6)
are the main representations of the structure
of the brain and biological
neurons. Assotsiativnaya pamyat i seti Koxonena.
3. INS training methods. Pravilo Xebba.
Perceptron and ego training. Principles of duality, rapid differentiation and methods
of optimization in training setey
raspoznavaniya obrazov, diagnostiki, upravleniya s pomoshchyu neyronnyx
Tipovÿe razdely i temy programmy po neyronnym setyam mogut
Neurosatellite expert systems (diagnostics, prediction, consultation)
neural network.
3) vladet osnovnymi sposobami resheniya prikladnyx zadach
4. Apply INS.
mathematics (linear algebra, mathematical physics).
neuroinformatics. Biological neuron seti: neurons, axons, dendrity,
synapses, doli
mozga, polushariya, mozjechok i ego structure, predvaritelnaya obrabotka
zritelnoy informatsii u lyagushki i koshki. Essay on the history of neuroinformatics.
Basic definitions for
neurocomputer
iskusstvennyx neyronnyx setey (INS). Elements INS. Obshchaya
analysis i dr.
Reshenie zadach optimizatsii s pomoshchyu INS (seti obratnogo
setey;
4) get skills in the development and implementation of software models
neurocomputer system; 5)
has a representation of modern achievements in development and
soderjat sleduyushchee:
1. Vvedenie. Principles of organization and operation of INS. The
idea of connectivity in the history of science. Basic directions in
neuronnyx experts).
Primery of medicine, economics, finance
rasprostraneniya oshibki).
Yavnoe formirovanie INS dlya resheniya nekotoryx zadach vÿchislitelnoy
system
Clear discriminant rules in the task of recognizing; discriminant
rasprostraneniya oshibki kak universalnye optimiziruyushchie ustroystva,
reshenie zadach diskretnoy optimizatsii s pomoshchyu setey Hopfilda, otsenka
characteristics of the principles of organization of information processes in INS.
Zadachi, reshaemÿe v nastoyashchee vremya s pomoshchyu neyronnyx setey. 2.
The obvious method of forming INS.
6
Machine Translated by Google
hierarchical INS. 5.
Reliable systems of unreliable elements.
speeds up the information processing process. In many cases sluchayax stanovitsya
iskusstvennogo intellekta. Obuchennaya na ogranichennom
mnojestve dannyx
navÿkov INS (ispolzovanie fluktuatsiy, vozrastayushchix v xode obucheniya, metod virtualnyx
setey). Vÿrabotka navÿkov, ustoychivyx k razrusheniyam chasti neyronnoy seti. Problem
ustoychivosti old navÿkov on otnosheniyu k vÿrabotke novyx. 6. Architecture and design of
neuroimitators (Realization INS). Problems of realization of INS. Methods of realization.
Software models
bolshom chisle mejneyronnyx soedineniy set priobretaet ustoychivost k
rezultaty na dannyx, ne ispolzovavshixsya v protsesse obucheniya.
application of technology sverxvysokoy stepeni integratsii. Differences
neurocomputers. 7.
Zaklyuchenie. Prospects for the development
and application of INS i
svyazey berut na sebya ispravnye linii, v rezultate chego deyatelnost seti
Do'stlaringiz bilan baham: 
