Methodology and Tools for Designing Binary Neural Networks

This paper presents results of a research in the field of software development, design methods, as well as training and synthesis of binary neural networks. The research is based on the model of a biomorphic neuron proposed by A.A. Zhdanov, which features noise immunity and is capable of forgetting...

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Veröffentlicht in:Programming and computer software Jg. 46; H. 1; S. 49 - 56
1. Verfasser: Stepanyan, I. V.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Moscow Pleiades Publishing 01.01.2020
Springer Nature B.V
Schlagworte:
Algorithms
Artificial Intelligence
Computer Science
Neural networks
Neurobiology
Neurons
Neurosciences
Operating Systems
Programmable logic devices
Software
Software development
Software development tools
Software Engineering
Software Engineering/Programming and Operating Systems
Source code
Syntax
Training
Visualization
ISSN:0361-7688, 1608-3261
Online-Zugang:Volltext
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Zusammenfassung:This paper presents results of a research in the field of software development, design methods, as well as training and synthesis of binary neural networks. The research is based on the model of a biomorphic neuron proposed by A.A. Zhdanov, which features noise immunity and is capable of forgetting and additional training. Software tools for designing and visualizing the modeling of binary neural structures are described. Use cases and features of a formal markup language for neural network models, as well as principles of generating deep learning structures, are discussed. A neural network markup language interpreter can automatically generate source code in Verilog with the description of the neural-like implementation of intelligent systems for software and hardware solutions on programmable logic devices (PLDs).
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0361-7688
1608-3261
DOI:10.1134/S0361768820010065