
Main / Innokenty Vasilyevich Semushin
Author: "Innokenty Vasilyevich Semushin"
Innokentiy Vasilyevich Semushin, Ulyanovsk State University, Doctor of Science in Engineering, Professor of Information Technology at Ulyanovsk State University. Memberships in Professional Organizations: IEEE Society; IEEE Control SystemsSociety. Author of papers, monographs, and textbooks; holds patents for inventions. Field of interest: Systems and signals theory; computational mathematics. [email: kentvsem@yandex.ru]I. Semushin,
Yulia Vladimirovna Tsyganova, Ulyanovsk State University, Doctor of Science in Physics and Mathematics, Professor of Information Technology at Ulyanovsk State University. Author of papers, a monograph, and textbooks; holds State Registration Certificates of computer programs. Field of interest: Parameter identification and adaptive filtering; numerically efficient algorithms for stochastic systems. [email: tsyganovajv@gmail.com]Y. Tsyganova


Numerical Aspects of Farend Crosstalk Cancellation in Vdsl Downstream
A complexity analysis of computations involved in two precoding methods  Zero Forcing (ZF) vs. a Simplified Linear (SL)  in the context of a Very highspeed Digital Subscriber Line (VDSL) is presented in this paper. For the ZFprecoding technique, eight computing strategies have been compared, four of which entail the explicit calculation of inverse normalized channel matrices and other four do not. In addition to this analysis, SLprecoder complexity  based on the approximate matrix inversionhas been estimated. Both methods solve the problem of full or partial farend crosstalk (FEXT) cancellation in VDSL downstream transmission. For this problem, the strategy avoiding the explicit matrix inversion was found to have the smallest number of multiplication/division operations. The analysis performed provides an opportunity for VDSLdesigners to justifiably select a computationally attractive precoding strategy taking into account the necessity of adaptive power control for the input signals to the DSLchannel from the Central Station. Vdslсистемы, vdslsystems, farend channel crosstalk, downlink data transmission, zeroforcing precoding, simplified linear precoding.



Sections: Mathematical modeling
Subjects: Mathematical modeling. 
Innokentiy Vasilyevich Semushin, Ulyanovsk State University, Doctor of Science in Engineering, Professor of Information Technology at Ulyanovsk State University. Memberships in Professional Organizations: IEEE Society; IEEE Control Systems Society; “Russian Professorial Assembly”. Author of papers, monographs and textbooks; holds patents for inventions. Field of Interest: systems theory, control. [email: kentvsem@yandex.ru]I. Semushin


Towards Robust Riccati Iterations for Lqgoptimal or Parameteradaptive Estimation and Control Processes
The paper aims at the development of robust and efficient computational algorithms for stochastic linear control based on scalarized squareroot implementations. In the capacity of starting point, it uses the classical (formal) solution to the control problem known from the threedecker monography Stochastic models, estimation, and control, Academic Press, 19791982, by Peter S. Maybeck. The mutually timeinverse Riccati iterations being a core part of the solution, are interpreted in a uniform notation as the twostage update processes. For them, a transition to the two kinds of scalarized algorithms  direct and inverse, is performed to introduce into consideration a scalarized filter and scalarized regulator and avail ourselves of the opportunity to go into the question of numerically stable squareroot computation designs for Riccati iterations. The paper demonstrates one possible configuration in the form of the Potterstyle algorithm. That establishes the new direction in constructing robust LQGregulators for control as being based on many advances in robust filtering. Lqgcontrol, squareroot algorithms, finitehorizon discretetime control, scalarization.



Sections: Mathematical modeling
Subjects: Mathematical modeling. 
Andrei Vladimirovich Tsyganov, Ulyanovsk State Pedagogical University named after I.N. Ulyanov, Candidate of Physics and Mathematics, Associate Professor at Ulyanovsk State Pedagogical University named after I.N. Ulyanov; an author of papers, monographs, and textbooks; holds State Registration Certificates of computer programs; interested in metaheuristic and hybrid algorithms of stochastic and discrete minimization. [email: andrew.tsyganov@gmail.com]A. Tsyganov, Innokentiy Vasilyevich Semushin, Ulyanovsk State University, Doctor of Science in Engineering, Professor of Information Technologies Department at Ulyanovsk State University; an author of papers, monographs, and textbooks; holds patents for inventions; interested in filtering and control under uncertainty. [email: kentvsem@yandex.ru]I. Semushin, Iuliia Vladimirovna Tsyganova, Ulyanovsk State University, Candidate of Physics and Mathematics, Associate Professor of the Information Technologies Department at Ulyanovsk State University; an author of papers, a monograph, and textbooks; holds State Registration Certificates of computer programs; interested in parameter identification, adaptive filtering, and numerically efficient algorithms for stochastic systems. [email: tsyganovajv@gmail.com]I. Tsyganova, Aleksei Vladimirovich Golubkov, Ulyanovsk State Pedagogical University named after I.N. Ulyanov, Candidate for the Master’s Degree of Ulyanovsk State Pedagogical University named after I.N. Ulyanov; an author of papers; holds State Registration Certificates of computer programs; interested in mathematical modelling and programming. [email: kr8589@gmail.com]A. Golubkov, Stanislav Dmitriievich Vinokurov, Ulyanovsk State Pedagogical University named after I.N. Ulyanov, Postgraduate Student at Ulyanovsk State Pedagogical University named after I.N. Ulyanov; an author of papers; holds State Registration Certificates of computer programs; interested in mathematical modelling and programming. [email: phoenixdragonvista@ya.ru]S. Vinokurov


Metaheuristic Algorithms in the Issue of Identification of the Moving Object Mathematical Model Parameters
The article considers issues on the calculation of an aircraft range capability on the basis of tactical radius data within different altitude and speed ranges. In some cases, it is necessary to calculate the enemy’s aircraft range capability. As a rule, such calculations do not have any documents, parameters (fuel flow rate and consumption per kilometre), and methodologies for fuel consumption calculation. Usually, open information sources also do not have any information about the enemy’s aircraft flight distance and time. Due to this fact, the need in indirect and approximate estimation of the enemy’s aircraft range capability with the use of information from public and common data is driven. Information about tactical radiuses within the enemy’s aircraft different altitude and speed ranges is the example of such public data. The proposed methodology for calculation of the enemy’s aircraft range capability allows to estimate the enemy’s capabilities in target attacks with 10% ratio error and can be used in combat management systems of surface ships and shorebased complexes. The methodology is also of great interest for operational and approximate estimation of own forces capabilities in case of the operational loading choice. More accurate calculations should be carries out on the basis of manuals on flight operation and time if such opportunity exists.



Sections: Mathematical modeling
Subjects: Mathematical modeling. 
Innokentiy Vasilyevich Semushin, Ulyanovsk State University, Doctor of Science in Engineering, Professor of Information Technology Department at Ulyanovsk State University (UlSU); graduated from V.I. Ul’ianov [Lenin] Leningrad Electrical Engineering Institute, “LETI”, Faculty of Automation Engineering and Computer Science (now Faculty of Computer Science and Technology); author of papers, monographs and textbooks; holds patents for inventions; is interested in filtering and control under uncertainty. [email: kentvsem@yandex.ru]I. Semushin


Straightaway Explicit Fir Programming Algorithm for Filtering, Smoothing, and Prediction
In this paper, we develop a straightaway explicit finite impulse response (FIR) programming algorithm for the filtering, smoothing, and prediction of signals containing a nonrandom component or their derivatives as an admissible alternative to previously known methods. The distinctive property of the algorithm is that it determines the FIR directly via the Chebyshev polynomials arising in the finite sample based quadratic approximation numerical analysis thus alleviating the problem of normal equations solution in the ordinary least squares (OLS) method. Using the Chebyshev polynomials gave an option of obtaining the following: short and explicit calculation formulae for FIR, i. e. for the conversion device weighting coefficients, including a possibility of estimating the signal derivatives; short formulae for filterpredictor smoothing factors; necessary memory size design procedure for filterpredictors of arbitrary astaticism order. Results obtained are useful for practical calculations when making a selection of filtering or prediction formula, i.e. while programming a FIR conversion device, and they can find practical use in adaptive devices. Firfilters, transversal filter structure, chebyshev polynomials, filtering, smoothing, prediction, quadratic approximations.



Sections: Mathematical modeling
Subjects: Mathematical modeling, Electrical engineering and electronics. 
Innokentiy Vasilyevich Semushin, Ulyanovsk State University, Doctor of Science in Engineering, Professor of Information Technology Department at Ulyanovsk State University (UlSU); an author of papers, monographs, and textbooks; holds patents for inventions; his field of interest includes filtering and control under uncertainty. [email: kentvsem@yandex.ru]I. Semushin, Yuliya Maksimovna Krolivetskaya, Ulyanovsk State University, Postgraduate student of Information Technology Department at Ulyanovsk State University; graduated from the Faculty of Mathematics and Information Technology of UlSU with the specialty in Applied Mathematics and Computer Science; her field of interest includes filtering and model parameter change point detection for stochastic systems. [email: juliakrolivetskaya@gmail.com]Y. Krolivetskaya, Elena Sergeevna Petrova, Ulyanovsk State University, Postgraduate student of Information Technology Department at UlSU; graduated from Mathematics and Information Technology Faculty of UlSU with the specialty in «Applied Mathematics and Computer Science»; her field of interest includes filtering and model parameter identification for stochastic systems. [email: ]E. Petrova


Kalman Filter Oriented Mathematical Model of the Steadycircle Path
The model of stochastic harmonic oscillator is used to approximate the steadycircle path. The main motif for the approach is to meet the model linearity requirement with respect to the state vector even for the raplex trajectories and so to make the standard (nonextended) Kalman filter strictly applicable avoiding its linearization. Stochastic harmonic oscillator, abrupt maneuvering, ship navigation in complex conditions, collision avoiding systems.



Sections: Mathematical modeling, calculi of approximation and software systems
Subjects: Mathematical modeling, Automated control systems, Architecture of ship's system, Operational research. 
Innokentiy Vasilyevich Semushin, Ulyanovsk State University, Doctor of Science in Engineering, Professor of Information Technology Department
at Ulyanovsk State University (UlSU); author of papers, monographs and textbooks; holds patents for inventions; is
interested in filtering and control under uncertainty [email: kentvsem @yandex. ru]I. Semushin, Yulia Vladimirovna Tsyganova, Ulyanovsk State University, Doctor of Philosophy in Physics and Mathematics, Associate Professor of Information
Technology Department at UlSU; author and coauthor of monograph, papers, and textbooks; is interested in parameter
identification, adaptive filtering, and numerically efficient algorithms for stochastic systems [email: tsyganovajv@
mail.ru]Y. Tsyganova, Natalia Dmitrievna Starostina, Ulyanovsk State University, postgraduate student of Information Technology Department at UlSU; graduated
from Mathematics and Information Technology Faculty of UlSU with the specialty in «Applied Mathematics»; is
interested in computational methods of estimation and control [email: kapelika88@mail.ru]N. Starostina




Sections: Mathematical modeling, calculi of approximations and software systems
Subjects: Mathematical modeling. 
Innokenty Vasilyevich Semushin, Ulyanovsk State University, Doctor of Engineering, Professor at the Chair 'Information Technology';
author of monographs, articles, textbooks, holds patents for inventions; is interested in filtering and control under uncertainty [email: kentvsem@yandex.ru]I. Semushin, Yulia Vladimirovna Tsyganova, Ulyanovsk State University, Candidate of Physics and Mathematics, Associate Professor at the Chair 'Information Technology'
author of a monograph, articles, textbooks and tutorials; is interested in parametric identification, adaptive filtering, numerically efficient algorithms for stochastic systems [email: tsyganovajv@mail.ru]Y. Tsyganova, Kliment Valeryevich Zakharov, Federal ResearchandProduction Center 'ResearchandProduction Association 'Mars', graduated from the Faculty of Mathematics and Information Technology of Ulyanovsk State University in the profession "Mathematical Support and Administration of Information Systems"; programmer;
author of papers in the field of maneuver detection for surface vessel; is interested in statistic applications and models, digital simulation and modeling, navigation and control systems [email: zaharovk@yandex.ru]K. Zakharov


Stable Filtering Algorithmsfor Shipnavigation and Control Systems
The article deals with integral filtering, stressing a computational aspect, and gives a brief survey of numerically stable algorithms based on the three mathematical ideas: factorization of positive definite (covariance and information) matrices, scalarization of vector measurements and orthogonalizaiton of block matrices. Their use suggests a new SquareRoot Extended Kalman Filter algorithm as applied to nonlinear task of seatarget movement analysis. The article also discusses the use of the actual algorithm for navigation and control of ships including collision avoidance. Computational estimation methods, leastsquares method, integral filtration, numerical stability, extended kalman filter, statistic applications and models, digital simulation and modeling.



Sections: Mathematical modeling, calculi of approximationsandsoftware systems
Subjects: Mathematical modeling, Automated control systems, Architecture of ship's system. 
Innokenty Vasilyevich Semushin, Ulyanovsk State University, Doctor of Engineering, Professor at the Chair 'Information Technology' of Ulyanovsk State University; author of papers, monographs; holds patents for inventions; is interested in diagnostics, filtering and control in stochastic systems under uncertain conditions. [email: kentvsem@yandex.ru]I. Semushin, Yulia Vladimirovna Tsyganova, Ulyanovsk State University, Candidate of Physics and Mathematics, Associate Professor at the Chair 'Information Technology' of Ulyanovsk State University; author of papers, a monograph, textbooks and tutorials; is interested in parametric identification of stochastic systems, adaptive filtering, development of numerically efficient algorithms of identification and adaptation in stochastic systems. [email: tsyganovajv@mail.ru]Y. Tsyganova


Parametric Identification of an Error Model for Inertial Navigation Systems
The paper deals with a solution to the problem of parametric identification for an error model of inertial navigation system (INS) using the Auxiliary Performance Index (API) method. It compares the two approaches to the API building: identification of steadystate filter parameters and identification of systemmodel parameters taking into account the dynamics of Riccati equations in Kalman filter. The authors also give comparison characteristics of the two approaches and results of the computational experiments. Parametric identification, adaptive filtering, auxiliary performance index (api), kalman filter.



Sections: Mathematical modeling, calculus of approximations and software systems
Subjects: Mathematical modeling. 
Innokenty Vasilyevich Semushin, Ulyanovsk State University, Doctor of Engineering, Professor of the Chair 'Information Technologies' at the Ulyanovsk State University; interested in diagnostics, filtering and control in stochastic systems under uncertain conditions; has papers, monographs, patents. [email: kentvsem@yandex.ru]I. Semushin, Yulia Vladimirovna Tsyganova, Ulyanovsk State University, Candidate of Physics and Mathematics, Associate Professor of the Chair Information Technologies at the Ulyanovsk State University; interested in parametric identification of stochastic systems, adaptive filtering, development of numerically efficient algorithms of system identification and adaptation; author of papers. [email: tsyganovajv@mail.ru]Y. Tsyganova


Adaptive Squareroot Covariance Algorithm for Filtering
The article proposes a new adaptive squareroot algorithm for filtering, being numerically stable regarding errors of rounding made by computers and allowing mapping of the identification processes for unknown parameters of linear stochastic system and adaptive evaluation of its state as per the method of auxiliary functional of quality. Adaptive filtering, parametric identification, kalman filter, squareroot covariance filter, additional functional of quality.



Sections: Mathematical modeling, calculi of approximations and software systems
Subjects: Mathematical modeling. 
