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- Iryna Turchenko, O. Osolinsky, +4 authors Myroslav Komar
- 2009 IEEE International Workshop on Intelligentâ€¦
- 2009

The neural network based method of individual conversion characteristic identification of multisensor using reduced number of its calibration/testing results is proposed in this paper. The proposed method is based on reconstruction of surface points of multisensor conversion characteristic by modular neural network. Each neural network module reconstructsâ€¦ (More)

- Pavlo Bykovyy, I. Maykiv, Iryna Turchenko, Orest Kochan, Vasyl Yatskiv, George Markowsky
- 2005 IEEE Intelligent Data Acquisition andâ€¦
- 2005

This paper describes the design of a low-cost network controller that can be used to interface sensors to security systems. This controller can use either a two-wired network interface with reconfigurable structure or an open optical channel for data communication with the network server. This design reduces the cost of data communication channels betweenâ€¦ (More)

- Iryna Turchenko, Volodymyr Kochan, Anatoly Sachenko
- 2005 IEEE Intelligent Data Acquisition andâ€¦
- 2005

The possibility of artificial neural network usage for recognition of a signal of a multi-parameter sensor (MPS), described by different mathematical models, is described in this paper. These mathematical models are developed for the cases, when MPS conversion characteristics have positive derivatives, negative derivatives and derivatives of different signâ€¦ (More)

- Iryna Turchenko, Volodymyr Kochan, Anatoly Sachenko
- 2006 International Conference - Modern Problemsâ€¦
- 2006

An approach of modular neural networks using for recognition of an output signal of multi-parameter sensor (MPS) is described in this paper. A simple mathematical model of MPS is presented. The structure schemes of single neural network and modular neural networks are designed. The experimental researches of both methods are fulfilled using MATLAB software,â€¦ (More)

- Roman V. Kochan, Volodymyr Kochan, Anatoly Sachenko, I. Maykiv, Iryna Turchenko, George Markowsky
- 2005 IEEE Instrumentationand Measurementâ€¦
- 2005

This paper presents the development of a network capable application processor (NCAP) compatible with the IEEE1451 standard. Its features are an online, remote, real-time reprogramming mode and support of high-speed interfaces. The high-speed interfaces are implemented using a FPGA (field-programmable gate array). A novel design using a configurationâ€¦ (More)

A method of individual conversion characteristic identification of multisensor using reduced number of its calibration/testing results is described in this paper. The proposed method is based on the neural-based reconstruction (approximation or prediction) of surface points of multisensor conversion characteristic. Each neural network module reconstructsâ€¦ (More)

- Iryna Turchenko, Volodymyr Kochan, +4 authors Domenico Grimaldi
- 2006 IEEE Instrumentation and Measurementâ€¦
- 2006

The possibility of artificial neural network usage for recognition of a signal of a multiparameter sensor (MPS), described by different mathematical models, is described in this paper. These mathematical models are developed for the cases, when MPS conversion characteristics have positive derivatives, negative derivatives and derivatives of different signâ€¦ (More)

- Iryna Turchenko, Volodymyr Kochan, Anatoly Sachenko
- 2007 4th IEEE Workshop on Intelligent Dataâ€¦
- 2007

A simulation model of a section of mine ventilation network is adapted for modelling sequential neural-based control scheme of mine airflow. The techniques of appropriate training set of neural network, its structure and training algorithm are described. The results of simulation modelling of this approach are presented.

- Nadiya Vasylkiv, Lesia Dubchak, Taras Lendyuk, Iryna Turchenko, Inna Shylinska, Marek Boguslav Aleksander
- 2017 9th IEEE International Conference onâ€¦
- 2017

The article suggests the implementation of the tasks distribution system for students testing considering grade point average and current progress. This system is based on fuzzy logic. Fuzzy system rules were constructed and the system was checked for correctness of functioning.

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