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• ANALYSIS OF STABILITY AND FEATURES OF PRACTICAL IMPLEMENTATION OF HOGENAUER FILTERS AS RECURSIVE DIGITAL FILTERS WITH FINITE IMPULSE RESPONSE

  I.Е. Moiseenko , S. P. Tarasov , I.I. Turulin

  37-46

  2025-10-01

  Abstract ▼

  The article considers the issues of stability of cascade integrator-comb (CIC) filters used in digital signal processing, including decimation and interpolation. A brief review of modern publications on the architectural optimization of CIC filters is given. The main attention is paid to increasing the stability of filters to the overflow of the bit grid, analyzing their stability and the method of synthesis of recursive FIR filters (filters with a finite impulse response). For a better understanding of the nature of the stability of CIC filters, the paper presents mathematical calculations illustrating the features of the accumulation of the constant component for various block configurations. A change in the structure of the CIC filter is proposed, consisting in the permutation of the integrator and comb filter blocks. It is proved that such a change prevents the accumulation of the constant component of the signal in the integrators and, therefore, eliminates the overflow of the bit grid due to the accumulation of the constant component in the integrator. This approach is based on the property of linear filters, according to which changing the order of inclusion does not affect the transfer function. amplitude-frequency characteristic, but in the case of digital implementations it allows to significantly reduce the probability of overflow. The possibilities of hardware and software implementation of such structures are considered from the point of view of minimizing the loss of accuracy and increasing the reliability of digital signal processing systems. It is proposed to use integers or numbers with a fixed point to eliminate the accumulation of quantization errors. In addition, a program in Python was developed that implements a CIC filter taking into account the stability of the constant component in the input signal and the accurate execution of operations. The obtained results are compared with modern approaches presented in scientific research in recent years. The proposed solutions can be useful in developing digital filters for systems with limited computing resources and increased stability requirements.

• ANALYSIS OF CERTAIN WEIGHT FUNCTIONS (WINDOWS) AND THEIR APPROXIMATIONS FOR IMPLEMENTATION OF CONTROLLED RECURSIVE LOW-PASS FILTERS WITH A FINITE IMPULSE RESPONSE ON THEIR BASIS

  T.V. Shushkevich , А.А. Morozov, I. I. Turulin

  2021-11-14

  Abstract ▼

  There are various types of weighting functions, the so-called windows in digital signal processing,
  such as rectangular (Dirichlet window), triangular (Bartlett window), Vallee-Poussin window,
  Kaiser-Bessel window, Barsilon-Temesh window, Hann, Bohman, Blackman, Gauss (Weierstrass),
  Dolph - Chebyshev, Hamming windows and many others and ideal characteristics of standard filters
  such as low-pass, high-pass, bandpass filters. The purpose of this review article is to determine the most
  suitable weighting function for implementation on its basis of a controlled recursive low-pass filter with
  a finite impulse response. This article presents an analysis of only some of the above windows and their
  approximations, namely the Dolph - Chebyshev window, the Gauss (Weierstrass) window and the
  Hamming window. In addition to the analysis, the synthesis of recursive filters with a finite impulse
  response for weighting data based on the selected windows and their approximations was considered.
  The method of synthesis of Dolph-Chebyshev windows is considered. The implementation of the Gauss
  (Weierstrass) window is considered. Methods for approximating the Hamming window and methods
  and several algorithms for developing filters with FIR in the form of this window are considered. The
  estimation of parameters dependencies some quick window of the maximum level of the side lobes.
  Based on the data obtained, conclusions were drawn about the selection of the most suitable and
  demonstrating maximum performance windows, suitable for implementation on its basis of a controlled
  recursive low-pass filter with a finite impulse response.

• THE MODULE FOR PREDICTING CONVERTER PARAMETERS BASED ON SPECIFIED AMPLITUDE-FREQUENCY CHARACTERISTICS

  V.I. Shlaev

  93-103

  2025-11-10

  Abstract ▼

  The article discusses the solution of the problem of developing converters based on specified amplitude-frequency characteristics. The main problem is to carry out a large number of measuring measures with changes in the parameters of the transducers to achieve the necessary amplitude-frequency characteristics, which leads to high time and resource costs for development. The analysis of the main parameters of the converters affecting the specified amplitude-frequency characteristics is carried out. The existing approaches, methods and algorithms for creating converters of the required characteristics are analyzed. The development of a module for predicting the parameters of electromechanical converters based on specified amplitude-frequency characteristics is described. The research objectives include the creation of structural-parametric and mathematical models for calculating the characteristics of converters at the design stage. An algorithm for training a model based on experimental data obtained during measurements is described. The use of machine learning methods to predict parameters minimizes the number of experiments performed and reduces the cost of developing converters. The proposed approach is based on the use of the relationship between the design parameters of the converters and their frequency characteristics. The gradient boosting algorithm is used to increase the accuracy of forecasting. The stages of data preparation for model training are presented. The learning process of the model is described. The results demonstrate a significant reduction in the modeling time of the converters: the use of the module makes it possible to speed up the process several times compared with the experimental approach. Predicting characteristics based on a model provides comparable accuracy with a larger amount of data. The findings of the study confirm the effectiveness of the proposed approach in the development of converters, reducing time and financial costs, increasing the accuracy of modeling and applicability in conditions of limited resources.