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Yerzhan, Assel
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Computer Science & IT Electrical & Electronics Engineering

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Drone direction estimation: phase method with two-channel direction finder Kozhabayeva, Indira; Yerzhan, Assel; Boykachev, Pavel; Manbetova, Zhanat; Imankul, Manat; Yauheni, Builou; Solonar, Andrey; Dunayev, Pavel
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp2779-2789

Abstract

This scientific article presents a block diagram of a two-channel radio direction finder that effectively uses the phase method to determine the direction of the signal source. The main attention is paid to the mathematical model of the formation of the cardioid radiation pattern of biconical antennas, which have unique directivity characteristics. These features significantly affect the accuracy and reliability of the bearing determination process. The developed algorithm aims to accurately determine the direction of motion of an unmanned aerial vehicle, especially in the context of a two-channel radio receiver and a five-element antenna system. This antenna system provides unique capabilities for increased resolution and directional accuracy. The article also touches on the issue of software implementation of the developed algorithm, which is aimed at increasing the number of generated bearing estimates in conditions of limited time for observing an unmanned aerial vehicle. Thus, the proposed method is of interest in the field of precision direction finding in the context of small unmanned vehicles.
Method for design and implementation of telecommunication devices for aircraft Yerzhan, Assel; Kozhabayeva, Indira; Manbetova, Zhanat; Boykachev, Pavel; Nauryz, Kanysh; Zhazykbaeva, Zhazira; Seitova, Zhadra; Aitzhanova, Nursulu
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 4: August 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i4.pp4183-4194

Abstract

This article highlights the importance of electrical filters in radio engineering devices, emphasizing their role in transmitting signals in the transparency band and suppressing signals in the stop band. We examined methods for designing frequency-selective circuits with lumped parameters, which, in general, are a complete field of radio engineering and allow the synthesis of devices of varying complexity. The focus of the article is the frequency region, where the distributed properties of the synthesized structures appear. The article also provides an overview of various methods for synthesizing ultra-high frequency (UHF) filters. It is emphasized that for low-pass filters a transition from a low-frequency prototype to a high-frequency representation is applied, which, despite the crudeness of the approach, provides satisfactory results that can be improved at the production stage. The article also discusses various methods for implementing bandpass filters on distributed elements, including the use of short-circuited and open-circuited stubs, as well as weak-coupled lines. In conclusion, the paper highlights the need to improve these methods to improve process accuracy and make filter designers more efficient in radio engineering.
Study of the characteristics of broadband matching antennas for fifth-generation mobile communications based on new composite materials Nakisbekova, Balausa; Yerzhan, Assel; Boykachev, Pavel; Manbetova, Zhanat; Imankul, Manat; Shener, Anar; Yermekbaev, Muratbek; Dunayev, Pavel
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 3: June 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i3.pp2885-2895

Abstract

The presented research aims to analyze in detail the characteristics of broadband matching antennas specifically designed for 5G mobile communications applications, with an emphasis on innovative composite materials. The study focuses on a compact planar loop antenna designed for use on smartphones, covering the LTE/WWAN frequency bands 824 to 960 MHz, 1,710 to 2,690 MHz, and 3,300 to 3,600 MHz for full coverage of modern 5G networks. Experimental and numerical methods are used to broadly analyze the frequency range associated with 5G networks. The features of the use of composite materials in the implementation of antenna devices in 5G technologies are noted. A broadband matching circuit (BMC) with elements with lumped parameters and a reduced sensitivity invariant has been synthesized. A 3D model of the adaptive selective surface controller (SSC) was developed using CST Studio. The study results highlight the benefits of new composite materials in improving the performance of 5G antennas. This research makes a significant contribution to the development of 5G technologies by optimizing antenna design for efficient data transmission in modern mobile networks and can be a valuable resource for engineers and designers working in this field.
Detection of heart pathology using deep learning methods Naizagarayeva, Akgul; Abdikerimova, Gulzira; Shaikhanova, Aigul; Glazyrina, Natalya; Bekmagambetova, Gulmira; Mutovina, Natalya; Yerzhan, Assel; Tanirbergenov, Adilbek
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i6.pp6673-6680

Abstract

In the directions of modern medicine, a new area of processing and analysis of visual data is actively developing - a radio municipality - a computer technology that allows you to deeply analyze medical images, such as computed tomography (CT), magnetic resonance imaging (MRI), chest radiography (CXR), electrocardiography and electrocardiography. This approach allows us to extract quantitative texture signs from signals and distinguish informative features to describe the heart's pathology, providing a personified approach to diagnosis and treatment. Cardiovascular diseases (SVD) are one of the main causes of death in the world, and early detection is crucial for timely intervention and improvement of results. This experiment aims to increase the accuracy of deep learning algorithms to determine cardiovascular diseases. To achieve the goal, the methods of deep learning were considered used to analyze cardiograms. To solve the tasks set in the work, 50 patients were used who are classified by three indicators, 13 anomalous, 24 nonbeat, and 1 healthy parameter, which is taken from the MIT-BIH Arrhythmia database.
Noisy image enhancements using deep learning techniques Daurenbekov, Kuanysh; Aitimova, Ulzada; Dauitbayeva, Aigul; Sankibayev, Arman; Tulegenova, Elmira; Yerzhan, Assel; Yerzhanova, Akbota; Mukhamedrakhimova, Galiya
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 1: February 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i1.pp811-818

Abstract

This article explores the application of deep learning techniques to improve the accuracy of feature enhancements in noisy images. A multitasking convolutional neural network (CNN) learning model architecture has been proposed that is trained on a large set of annotated images. Various techniques have been used to process noisy images, including the use of data augmentation, the application of filters, and the use of image reconstruction techniques. As a result of the experiments, it was shown that the proposed model using deep learning methods significantly improves the accuracy of object recognition in noisy images. Compared to single-tasking models, the multi-tasking model showed the superiority of this approach in performing multiple tasks simultaneously and saving training time. This study confirms the effectiveness of using multitasking models using deep learning for object recognition in noisy images. The results obtained can be applied in various fields, including computer vision, robotics, automatic driving, and others, where accurate object recognition in noisy images is a critical component.
Using modified Chebyshev functions for approximation in 5G technologies Yerzhan, Assel; Nakisbekova, Balausa; Manbetova, Zhanat; Boykachev, Pavel; Imankul, Manat; Dzhanuzakova, Raushan; Shedreyeva, Indira; Karnakova, Gaini
International Journal of Electrical and Computer Engineering (IJECE) Vol 14, No 6: December 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v14i6.pp6508-6518

Abstract

This research addresses the critical challenge of broadband matching in radio engineering, focusing on enhancing phase-frequency response (PFC) linearity across wide frequency bands. A novel approach, utilizing modified Chebyshev functions, demonstrates significant potential in reducing phase distortions within 5G technology applications. Unlike traditional Chebyshev functions, this method incorporates strategically placed transmission zeros— complex conjugate pairs on the s-variable complex plane—without increasing the filter circuit's order. This innovation results in a low-order filter circuit characterized by uniform phase response and group delay characteristics (GDT), offering an effective solution for matching circuit design with less phase-frequency distortion and improved group delay uniformity across diverse load conditions. The modified Chebyshev approximation outperforms its classical counterpart in both phase linearity and selectivity within the 1 to 1.2 cutoff frequency range. This enhancement is crucial for the development of low-frequency filters, with broader implications for creating high-frequency, band-pass, and band-stop filters via known frequency transformations. Empirical results validate the proposed method's reliability and effectiveness, marking a significant advancement in the field of radio engineering by addressing broadband matching challenges with increased efficiency and simplified design implementations.
Method of undetermined coefficients for circuits and filters using Legendre functions Manbetova, Zhanat; Dunayev, Pavel; Yerzhan, Assel; Imankul, Manat; Zhazykbayeva, Zhazira; Seitova, Zhadra; Dzhanuzakova, Raushan; Karnakova, Gayni
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp846-854

Abstract

This article presents a new way to implement matching networks and filters using the method of undetermined coefficients. A method is proposed for approximating the transmission coefficient of the synthesized filter, taking into account the required amplitude-frequency characteristics. To synthesize the filter, an approximating function (AF) was used using orthogonal Legendre polynomials, which is a mathematical description using a system of equations. Filter properties whose implementation is based on modified Legendre approximating functions usually depend on the interval on which they are defined and have the property that they are orthogonal on this interval. An example of seventh order filter synthesis using modified Legendre approximating functions is given. The filter circuit is implemented, the elements of the filter circuit are calculated based on the selected approximating modified function. The criteria used were minimization of the unevenness of the group delay time (GDT) and minimization of the complex approximation error for given values of the AF parameters. As a result, the number of filter elements, the group delay value and the complex approximation error are significantly reduced.
Co-Authors Abdikerimova, Gulzira Aitimova, Ulzada Aitzhanova, Nursulu Bekmagambetova, Gulmira Boykachev, Pavel Dauitbayeva, Aigul Daurenbekov, Kuanysh Dunayev, Pavel Dzhanuzakova, Raushan Glazyrina, Natalya Imankul, Manat Karnakova, Gaini Karnakova, Gayni Kozhabayeva, Indira Manbetova, Zhanat Mukhamedrakhimova, Galiya Mutovina, Natalya Naizagarayeva, Akgul Nakisbekova, Balausa Nauryz, Kanysh Sankibayev, Arman Seitova, Zhadra Shaikhanova, Aigul Shedreyeva, Indira Shener, Anar Solonar, Andrey Tanirbergenov, Adilbek Tulegenova, Elmira Yauheni, Builou Yermekbaev, Muratbek Yerzhanova, Akbota Zhazykbaeva, Zhazira Zhazykbayeva, Zhazira