RU2003115682A - NEURAL NETWORK FOR CALCULATING THE POSITIONAL CHARACTERISTICS OF THE NUMBER RANGE REPRESENTED IN THE RESIDUAL CLASS SYSTEM - Google Patents

NEURAL NETWORK FOR CALCULATING THE POSITIONAL CHARACTERISTICS OF THE NUMBER RANGE REPRESENTED IN THE RESIDUAL CLASS SYSTEM

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Publication number
RU2003115682A
RU2003115682A RU2003115682/09A RU2003115682A RU2003115682A RU 2003115682 A RU2003115682 A RU 2003115682A RU 2003115682/09 A RU2003115682/09 A RU 2003115682/09A RU 2003115682 A RU2003115682 A RU 2003115682A RU 2003115682 A RU2003115682 A RU 2003115682A
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RU
Russia
Prior art keywords
neural network
calculating
number range
range represented
class system
Prior art date
Application number
RU2003115682/09A
Other languages
Russian (ru)
Other versions
RU2271569C2 (en
Inventor
Николай Иванович Червяков
Руслан Васильевич Ткачук
Original Assignee
Николай Иванович Червяков
Руслан Васильевич Ткачук
Filing date
Publication date
Application filed by Николай Иванович Червяков, Руслан Васильевич Ткачук filed Critical Николай Иванович Червяков
Priority to RU2003115682/09A priority Critical patent/RU2271569C2/en
Priority claimed from RU2003115682/09A external-priority patent/RU2271569C2/en
Publication of RU2003115682A publication Critical patent/RU2003115682A/en
Application granted granted Critical
Publication of RU2271569C2 publication Critical patent/RU2271569C2/en

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Claims (1)

Нейронная сеть для вычисления позиционной характеристики, ранга числа, представленного в системе остаточных классов, содержащая входной слой нейронов, нейронную сеть конечного кольца отличающаяся тем, что с целью сокращения объема оборудования и повышения скорости выходы нейронов входного слоя посредством весовых коэффициентов соединены с входами нейронной сети конечного кольца, выходы которой являются выходами нейронной сети.A neural network for calculating the positional characteristic, rank of the number represented in the system of residual classes, containing an input layer of neurons, a finite ring neural network characterized in that, in order to reduce the amount of equipment and increase the speed, the outputs of the input layer neurons are connected to the inputs of the final neural network rings, the outputs of which are outputs of the neural network.
RU2003115682/09A 2003-05-26 2003-05-26 Neuron network for calculating positional characteristic rank of number, represented in remainder classes system RU2271569C2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
RU2003115682/09A RU2271569C2 (en) 2003-05-26 2003-05-26 Neuron network for calculating positional characteristic rank of number, represented in remainder classes system

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
RU2003115682/09A RU2271569C2 (en) 2003-05-26 2003-05-26 Neuron network for calculating positional characteristic rank of number, represented in remainder classes system

Publications (2)

Publication Number Publication Date
RU2003115682A true RU2003115682A (en) 2004-11-20
RU2271569C2 RU2271569C2 (en) 2006-03-10

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RU2003115682/09A RU2271569C2 (en) 2003-05-26 2003-05-26 Neuron network for calculating positional characteristic rank of number, represented in remainder classes system

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RU (1) RU2271569C2 (en)

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
RU2470365C1 (en) * 2011-10-31 2012-12-20 Александр Алексеевич Бурба Apparatus for technical and economic assessment of scientific research and development works
RU2613022C1 (en) * 2015-10-22 2017-03-14 Негосударственное частное образовательное учреждение высшего образования "Московский институт экономики, политики и права" (НЧОУ ВО "МИЭПП"") Device for techno-economic evaluating research and development work
RU2759964C1 (en) * 2020-08-12 2021-11-19 Федеральное государственное казенное военное образовательное учреждение высшего образования "Военный учебно-научный центр Военно-воздушных сил "Военно-воздушная академия имени профессора Н.Е. Жуковского и Ю.А. Гагарина" (г. Воронеж) Министерства обороны Российской Федерации Finite ring neural network

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