Papers by Igor Lazarowych
Èlektronnoe modelirovanie, 2019
Zenodo (CERN European Organization for Nuclear Research), Jun 12, 2020
Scientific journal of the Ternopil national technical university
An analysis of the well-known distance education systems was made, which allowed us to highlight ... more An analysis of the well-known distance education systems was made, which allowed us to highlight their advantages and disadvantages and identify some ways to improve the program by adding adaptive functionality and interactivity, aimed at improving the educational process quality. An interface for working with the system for different groups of users (students, teachers, developers) has been developed whose use allows you to download study materials and test tasks conveniently, to edit and adapt some meaningful links between information sections (Units), to pass training and test control, to form final reports of success and recommendations for further learning steps. The multi-set method of assessing the level of study of content units was described and the adaptive functionality of forming the content of educational lectures for review or in-depth mastering of the theoretical content was presented, which allows taking into account the initial level of student knowledge and his/her...
CERN European Organization for Nuclear Research - Zenodo, Jun 12, 2020
2018 14th International Conference on Advanced Trends in Radioelecrtronics, Telecommunications and Computer Engineering (TCSET)
The article examines implementation features of variable entropy random signals processing in the... more The article examines implementation features of variable entropy random signals processing in the computer system communication channels. An optimization of calculating entropy estimations algorithm was proposed. This algorithm is not require using of Taylor series decomposition as a part of the calculation process.
2020 IEEE 7th International Conference on Energy Smart Systems (ESS)
In this paper we proposed the use of JT65A radio communication protocol for data exchange in wide... more In this paper we proposed the use of JT65A radio communication protocol for data exchange in wide-area monitoring systems in electric power systems. We investigated the software demodulation of the multiple frequency shift keying weak signals transmitted with JT65A communication protocol using deep convolutional neural network. We presented the demodulation performance in form of symbol and bit error rates. We focused on the interference immunity of the protocol over an additive white Gaussian noise with average signal-to-noise ratios in the range from −30 dB to 0 dB, which was obtained for the first time. We proved that the interference immunity is about 1.5 dB less than the theoretical limit of non-coherent demodulation of orthogonal MFSK signals.
This paper proposes a method for reducing data redundancy using a randomization procedure. The me... more This paper proposes a method for reducing data redundancy using a randomization procedure. The method can be effectively applied before transmitting or storing information in automation systems in various fields of communication systems and networks.
Digital communications techniques based on random, chaotic, or noisy carriers are well known and ... more Digital communications techniques based on random, chaotic, or noisy carriers are well known and successfully used in a number of applications. Simple on-off or amplitude shift noise keying modulation schemes are among the most popular. In this paper, we propose to use a classification model based on an artificial dense neural network and a deep learning approach for software-defined demodulation of spread spectrum signals.
The conference paper presents the method for determining the quality characteristics and sub-char... more The conference paper presents the method for determining the quality characteristics and sub-characteristics weights. It improves the methods specified in international standards and makes practical use possible for evaluating the quality of a software product.
This paper presents an overview of the cryptographic algorithm visualization possibilities of the... more This paper presents an overview of the cryptographic algorithm visualization possibilities of the CrypTool. The AES cipher is used as an example. Visualization tools for modern cryptographic algorithms in CrypTool make it possible to track the content of cryptographic transforms at every step. This makes it easier to understand the complex algorithms in software development.
2020 IEEE International Conference on Problems of Infocommunications. Science and Technology (PIC S&T), 2020
Digital communications techniques based on random, chaotic, or noisy carriers are well known and ... more Digital communications techniques based on random, chaotic, or noisy carriers are well known and successfully used in a number of applications. Simple on-off or amplitude shift noise keying modulation schemes are among the most popular. In this paper 1, we propose to use a classification model based on an artificial dense neural network and a deep learning approach for software-defined demodulation of amplitude noise shift keying spread spectrum signals. The main challenge with processing of such signals is that statistical properties of signal and interference are very similar. The aim of the research is to proof the feasibility of the proposed technique and to obtain the noise-immunity metrics. The methodology of the research is to evaluate the deep learning demodulation model pre-trained on the artificially synthesized dataset. The dataset contains the automatically labeled mixtures of noise carrier signals with additive white Gaussian interferences. The average signal-to-noise ratios in the dataset range from -30 dB to 0 dB. The numerical results from simulations are used to evaluate the demodulation performance. We present the demodulation performance as symbol and bit error rates and compare results with other well-known approaches. The paper reports noise immunity greater than immunity of “power reception” method at least for 3.5 dB. In addition, we assessed the time complexity and proved real-time processing capability.
2021 IEEE 3rd Ukraine Conference on Electrical and Computer Engineering (UKRCON), 2021
This paper presents a new method for noise-immune demodulation of BPSK signals. It is based on th... more This paper presents a new method for noise-immune demodulation of BPSK signals. It is based on the use of an artificial neural network and signal randomization. Signal randomization increases self-synchronization properties and simplifies timing techniques. The demodulator model was designed and implemented in software. The demodulation bit error rate and standard deviation of normalized timing error were studied as a function of the signal-to-noise ratio. It was found out that the use of randomization reduces the normalized timing error by 7.5% at the normalized signal-to-noise ratio value of −15 dB. The method can be used to digital exchange data under strong interference conditions, in particular, in computer telecommunication systems, medical equipment, industrial networks, smart sensor networks and satellite communications.
Innovations in Smart Cities Applications Volume 4, 2021
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Papers by Igor Lazarowych