Multivariate analysis and optimization of linear periodically time-variable circuits at the enviroment of MAOPCs

Authors

  • Yu. I. Shapovalov Lviv Polytechnic National University, Lviv, Ukraine
  • B. A. Mandziy Lviv Polytechnic National University, Lviv, Ukraine
  • D. R. Bachyk Lviv Polytechnic National University, Lviv, Ukraine

DOI:

https://doi.org/10.20535/RADAP.2015.60.34-44

Keywords:

LPTV circuits, frequency symbolic method, multivariate analysis

Abstract

Introduction. The architecture of MAOPCs functions system and examples of its application for solving the tasks of multivariate analysis of linear periodically time-variable (LPTV) circuits based on the frequency symbolic method are considered in this paper. The method is based on approximation of transfer functions of LPTV circuits in the form of trigonometric polynomials of the Fourier. The MAOPCs functions system is implemented in the environment of MATLAB. Architecture and functions of the system MAOPCs. The system consists of 17 functions that are implemented in the environment of MATLAB. Each function has arguments and global variables and carries out over them identified transformation. Functions and global variables form the input data program for research LPTV circuit and should be defined (set) at the time of calling the function. Conclusions. The MAOPCs functions system enables to investigate LPTV circuits, setting in program input data the algorithms for their research and to use a strong symbolic apparatus and other standard functions of the package MATLAB in full, without understanding the deep of mathematical apparatus of implemented methods.

Author Biographies

Yu. I. Shapovalov, Lviv Polytechnic National University, Lviv

Shapovalov Yu. I., Sc.D., Associate Professor

B. A. Mandziy, Lviv Polytechnic National University, Lviv

Mandziy B.A., Sc.D., Professor

D. R. Bachyk, Lviv Polytechnic National University, Lviv

Bachyk D. R., Ph.D.

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Published

2015-03-30

Issue

60

Section

Computing methods in radio electronics

License

Copyright (c) 2020 Yu. I. Shapovalov, B. A. Mandziy, D. R. Bachyk

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