Single-frame image super-resolution based on singular square matrix operator
Y Rashkevych, D Peleshko… - 2017 IEEE First …, 2017 - ieeexplore.ieee.org
In the paper the method of single-frame image super-resolution based on the singular
decomposition of matrix operator of the convergence square matrix operator is proposed …
decomposition of matrix operator of the convergence square matrix operator is proposed …
Bithreshold neural network classifier
The fully connected 2-layer feedforward network architecture with the hidden layer
consisting of bithreshold neurons is considered in the paper. We design the neural network …
consisting of bithreshold neurons is considered in the paper. We design the neural network …
Representational capabilities and learning of bithreshold neural networks
V Kotsovsky, A Batyuk - … “Intellectual Systems of Decision Making and …, 2020 - Springer
The paper deals with questions related to the ability of real-weighted bithreshold neurons
and neural networks to solve the classification tasks. We study how many partitions of a finite …
and neural networks to solve the classification tasks. We study how many partitions of a finite …
Streaming process discovery for lambda architecture-based process monitoring platform
A Batyuk, V Voityshyn - 2018 IEEE 13th International Scientific …, 2018 - ieeexplore.ieee.org
Having precise information about how business processes are performed in real-life is an
important competitive advantage for a modern company. The digital footprint left by …
important competitive advantage for a modern company. The digital footprint left by …
Method and means of symmetric real-time neural network data encryption
The training of the auto-associative neural network by the method of principal components
analysis has been conducted and the matrix of weight coefficients has been calculated. A …
analysis has been conducted and the matrix of weight coefficients has been calculated. A …
A non-iterative neural-like framework for missing data imputation
The paper presents developed by the authors a non-iterative, neural-like framework for
filling missing data. This framework applies the high-speed linear neural-like structure using …
filling missing data. This framework applies the high-speed linear neural-like structure using …
Dictionary data structure for a text analysis task using cross-references
A Yarovyi, D Kudriavtsev - 2022 IEEE 17th International …, 2022 - ieeexplore.ieee.org
In this research, the dictionary structure of data for storing text data is considered. The main
characteristics of the analysis of textual information by thematic classification are defined …
characteristics of the analysis of textual information by thematic classification are defined …
The generalized shift operator and non-harmonic signal analysis
I Dronyuk, O Fedevych… - 2017 14th International …, 2017 - ieeexplore.ieee.org
The generalized shift operator and non-harmonic signal analysis Page 1 89 CADSM 2017,
21-25 February, 2017, Polyana-Svalyava (Zakarpattya), UKRAINE The Generalized Shift …
21-25 February, 2017, Polyana-Svalyava (Zakarpattya), UKRAINE The Generalized Shift …
Neural-like real-time data protection and transmission system
It is proposed to develop a neural-like system of real-time data protection and transmission
using an integrated approach, which includes: research and development of theoretical …
using an integrated approach, which includes: research and development of theoretical …
Development of modules of neuro-like cryptographic encryption and decryption of data and their implementation on FPGA
The requirements are formed and the main stages of synthesis of cryptological encryption
and data decryption modules are explained. The tabular-algorithmic method of scalar …
and data decryption modules are explained. The tabular-algorithmic method of scalar …