ISSN 1991-2927
 

ACP № 1 (55) 2019

Author: "Aleksandr Grigorievich Tashlinskii"

Aleksandr Grigorevich Tashlinskii, Ulyanovsk State Technical University, Doctor of Engineering, Professor; graduated from the Faculty of Radioengineering of Ulyanovsk Polytechnic Institute; Head of the Department of Radioengineering at Ulyanovsk State Technical University; an author of articles, monographs, and inventions in the field of digital signal and image processing. [e-mail: tag@ulstu.ru]A. Tashlinskii,

Mikhail Grigorevich Tsarev, Ulyanovsk State Technical University, Postgraduate Student at Ulyanovsk State Technical University; graduated from the Faculty of Radioengineering of Ulyanovsk State Technical University; an author of articles in the field of digital signal and image processing. [e-mail: michael.tsaryov@gmail.com]M. Tsarev

Pseudogradient Time Shift Estimation of Radio Pulses Received By Spatially Distributed Sensors Using Fpld 000_13.pdf

The authors carried out the analysis of computational complexity and performance of recurrent algorithms for estimation of the difference in arrival times of radio pulses received by spatially distributed sensors such as antenna array elements in case of their realization on field programmable logic devices (FLPD). The algorithms are synthesized on the basis of non-identification pseudogradient adaptation; they do not require any prior assessment of the signal parameters. The algorithms are stable to impulse interference and used under conditions of prior uncertainty. The problem of measuring the time shift is considered as the problem of estimating the parameter of alignment of signals received by different receivers and digitized. The specificity of the algorithms implementation in VHDL in case of concerning mean square frame-to-frame difference as a target function is considered. An implementation of one of the algorithm operations (linear interpolation of discrete signal) on FPLD is shown as an example. The algorithm, the block diagram, the module diagram, and the comparative analysis of the achievable frequency for different types of FPLD are presented in the article.

Digital signal, radiolocation, spatially distributed sensors, time shift, pseudogradient estimation, target function, fpld.

2016_ 2

Sections: Electronic and electrical engineering

Subjects: Electrical engineering and electronics, Automated control systems, Architecture of ship's system.


Aleksandr Grigorievich Tashlinskii, Ulyanovsk State Technical University, Doctor of Engineering, Professor; graduated from the Faculty of Radioengineering at Ulyanovsk Polytechnic Institute; Head of the Department of Radioengineering at Ulyanovsk State Technical University; an author of articles, monographs, and inventions in the field of signals and images digital processing. [e-mail: tag@ulstu.ru]A. Tashlinskii,

Pavel Victorovich Smirnov, Ulyanovsk State Technical University, graduated from the Faculty of Radioengineering at Ulyanovsk State Technical University; Post-Graduate Student at the same university; an author of articles in the field of estimation of parameters interframe geometric deformations. [e-mail: rtcis@mail.ru]P. Smirnov

Pixel-by-pixel Interframe Geometric Image Deformation Estimation in Assigning the Moving Object Area 39_6.pdf

The comparative analysis of different variants of implementation of pixel-by-pixel interframe geometric image deformation estimation by the example of the task intended for assigning the moving object area has been carried out in this paper. The projections and polar parameters of the reference image have been studied as estimated parameters of shift vectors of its points corresponding to the nodes. Two estimation techniques for the shift vectors field are proposed. In the first case, a pseudogradient algorithm sequentially processes all nodes of the reference image line by line. Each line is processed by the pseudogradient algorithm bidirectionally (“from left to right” and “from right to left”). The coprocessing of results allows compensating the inertia of the recursive estimation. The second technique studies the possibility to increase the processing efficiency by taking into account the correlation of image adjacent lines. The lines are processed one after the other with change in direction after each line. The resultant estimation is made of two values received for each node of the reference image. Two criteria for making the estimation are researched, namely Mean square difference and correlation coefficient. The computational effect is estimated in implementing the techniques proposed.

Digital image, interframe geometric deformations, moving object assignment, pseudogradient algorithm, objective function.

2015_ 1

Sections: Mathematical modeling

Subjects: Mathematical modeling, Artificial intelligence.


Aleksandr Grigorievich Tashlinskii, Ulyanovsk State Technical University, Doctor of Engineering, Professor; graduated from the Faculty of Radio Engineering at Ulyanovsk State Technical University; Deputy Head of Radio Engineering Department at Ulyanovsk State Technical University; an author of articles, monographs, and inventions in the field of digital processing of signals and images. [e-mail: tag@ulstu.ru]A. Tashlinskii,

Sergey Vasilievich Voronov, Ulyanovsk State Technical University, graduated from the Faculty of Radio Engineering of Ulyanovsk State Technical University; a post-graduate student of the same University; an author of articles in the field of estimation of parameters of geometric image deformations. [e-mail: valmedia@yandex.ru]S. Voronov

Use of Mutual Information As Objective Function of Image Parameter Quality Estimation 37_5.pdf

Mutual information is considered as the objective function of recursive image parameters’ estimation. A new approach reducing the computational cost to the image entropy estimation based on cross-validation procedure is proposed. The article offers an analysis of ways to reduce the error of mutual information gradient estimation, at this, the Parzen-window method is used for image brightness probability density estimation.

Digital image, objective function, mutual information, image entropy, cross-validation, optimization, stochastic gradient.

2014_ 3

Sections: Mathematical modeling

Subjects: Mathematical modeling, Artificial intelligence, Architecture of ship's system.


Aleksandr Grigorevich Tashlinskii, Ulyanovsk State Technical University, Doctor of Engineering, Professor, graduated from the Faculty of Radio-Engineering at Ulyanovsk Polytechnic Institute; Head of the Department of Radio-Engineering at Ulyanovsk State Technical University; an author of articles, monographs, and inventions in the field of digital processing of signals and images. [e-mail: tag@ulstu.ru]A. Tashlinskii,

Sergey Vasilievich Voronov, Ulyanovsk State Technical University, graduated from the Faculty of Radio-Engineering at Ulyanovsk State Technical University, Post-graduate student at the same University; an author of articles in the field of estimation of interframe geometric image deformations. [e-mail: valmedia@yandex.ru]S. Voronov,

Ilia Vasilevich Voronov, Ulyanovsk State Technical University, graduated from the Faculty of Radio-Engineering at Ulyanovsk State Technical University, Post-graduate student at the same University; an author of articles in the field of recurrent estimation of digital image parameters. [e-mail: ilvo1987@gmail.com]I. Voronov

Analysis of Objective Functions in a Problem of Estimation of Mutual Geometric Image Deformations 34_5.pdf

A convergence analysis of stochastic gradient estimation procedures without identification for the problem of the image mutual geometric deformation estimation is fulfilled. Interframe correlation coefficient, mean squared frame-to-frame difference and mutual information are considered as objective function

Image deformations’ estimation, objective function, correlation coefficient, mean squared frame-to-frame difference, mutual information.

2013_ 4

Sections: Mathematical modeling, calculi of approximation and software systems

Subjects: Mathematical modeling.


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